Triple
T281876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dutch guilder |
E5370
|
entity |
| Predicate | ISO4217Code |
P189
|
FINISHED |
| Object |
NLG
NLG was the ISO 4217 currency code for the Dutch guilder, the former national currency of the Netherlands before the adoption of the euro.
|
E36858
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: NLG | Statement: [Dutch guilder, ISO4217Code, NLG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NLG Context triple: [Dutch guilder, ISO4217Code, NLG]
-
A.
NLS
NLS (oN-Line System) was an early, pioneering computer system that introduced many foundational concepts of modern computing, including the mouse, hypertext, and collaborative editing.
-
B.
NLS
NLS is a U.S. Library of Congress program that provides free accessible reading materials, including braille and audio books, to people who are blind, have low vision, or are print disabled.
-
C.
Grok
Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
-
D.
Versoix
Versoix is a Swiss municipality on the shores of Lake Geneva, known as a residential suburb of Geneva with lakeside promenades and a mix of urban and natural landscapes.
-
E.
GPT-3
GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: NLG Triple: [Dutch guilder, ISO4217Code, NLG]
Generated description
NLG was the ISO 4217 currency code for the Dutch guilder, the former national currency of the Netherlands before the adoption of the euro.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NLG Target entity description: NLG was the ISO 4217 currency code for the Dutch guilder, the former national currency of the Netherlands before the adoption of the euro.
-
A.
NLS
NLS (oN-Line System) was an early, pioneering computer system that introduced many foundational concepts of modern computing, including the mouse, hypertext, and collaborative editing.
-
B.
NLS
NLS is a U.S. Library of Congress program that provides free accessible reading materials, including braille and audio books, to people who are blind, have low vision, or are print disabled.
-
C.
Grok
Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
-
D.
Versoix
Versoix is a Swiss municipality on the shores of Lake Geneva, known as a residential suburb of Geneva with lakeside promenades and a mix of urban and natural landscapes.
-
E.
GPT-3
GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25e0a23c0819083abee28b2dea49c |
completed | Feb. 28, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a399a74d448190a4857ce008e64e7e |
completed | March 1, 2026, 1:43 a.m. |
| NEDg | Description generation | batch_69a39a161064819096fd8f4efe533538 |
completed | March 1, 2026, 1:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a39a7c0cec81909f737bd963ad306d |
completed | March 1, 2026, 1:46 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.