Triple
T9012487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teochew people |
E215507
|
entity |
| Predicate | romanizationSystem |
P6517
|
FINISHED |
| Object |
Pengim
Pengim is a romanization system used to represent the sounds of the Teochew (Chaozhou) Chinese dialect with the Latin alphabet.
|
E773614
|
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: Pengim | Statement: [Teochew people, romanizationSystem, Pengim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pengim Context triple: [Teochew people, romanizationSystem, Pengim]
-
A.
Peng
Peng is a Chinese surname borne by numerous notable figures in politics, arts, and academia throughout Chinese history and the modern era.
-
B.
Pangim
Pangim, also known as Panaji, is the riverside city that serves as the administrative and cultural center of the Indian state of Goa.
-
C.
Pimampiro
Pimampiro is a small town and canton in northern Ecuador known for its agricultural production and Andean highland landscapes.
-
D.
Penge
Penge is a suburban district in southeast London known for its Victorian architecture and proximity to Crystal Palace.
-
E.
Shom Peng
Shom Peng is an indigenous language spoken by the Shompen people of Great Nicobar Island in India’s Nicobar Islands.
- 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: Pengim Triple: [Teochew people, romanizationSystem, Pengim]
Generated description
Pengim is a romanization system used to represent the sounds of the Teochew (Chaozhou) Chinese dialect with the Latin alphabet.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pengim Target entity description: Pengim is a romanization system used to represent the sounds of the Teochew (Chaozhou) Chinese dialect with the Latin alphabet.
-
A.
Peng
Peng is a Chinese surname borne by numerous notable figures in politics, arts, and academia throughout Chinese history and the modern era.
-
B.
Pangim
Pangim, also known as Panaji, is the riverside city that serves as the administrative and cultural center of the Indian state of Goa.
-
C.
Pimampiro
Pimampiro is a small town and canton in northern Ecuador known for its agricultural production and Andean highland landscapes.
-
D.
Penge
Penge is a suburban district in southeast London known for its Victorian architecture and proximity to Crystal Palace.
-
E.
Shom Peng
Shom Peng is an indigenous language spoken by the Shompen people of Great Nicobar Island in India’s Nicobar Islands.
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69f846f88190af65dfcf8bdd936a |
completed | April 1, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdba11a6481909cac624530a77ffe |
completed | April 3, 2026, 3:24 p.m. |
| NEDg | Description generation | batch_69cfdc9868fc8190addad6b87b567277 |
completed | April 3, 2026, 3:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfe0aafe4c81908a5b31590f6c9152 |
completed | April 3, 2026, 3:45 p.m. |
Created at: March 30, 2026, 7:06 p.m.