Triple
T16541086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ensign, United States Coast Guard |
E401819
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
ENS
ENS is the standard abbreviation for the junior commissioned officer rank of Ensign in the United States Coast Guard.
|
E1219904
|
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: ENS | Statement: [Ensign, United States Coast Guard, abbreviation, ENS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ENS Context triple: [Ensign, United States Coast Guard, abbreviation, ENS]
-
A.
ENS
ENS is a common abbreviation for the École Normale Supérieure, a prestigious French grande école known for its elite training in the sciences and humanities.
-
B.
ENE
ENE was the stock ticker symbol for Enron Corporation, the American energy company infamous for its massive accounting fraud and subsequent 2001 bankruptcy.
-
C.
ENA
ENA is a prestigious French grande école that trained many of the country’s top civil servants and political leaders.
-
D.
ESS
ESS is the commonly used abbreviation for the European Standardization System, the framework through which European standards are developed and harmonized.
-
E.
ESS
ESS is the commonly used abbreviation for Étoile Sportive du Sahel, a prominent multi-sport club based in Sousse, Tunisia, best known for its successful football team.
- 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: ENS Triple: [Ensign, United States Coast Guard, abbreviation, ENS]
Generated description
ENS is the standard abbreviation for the junior commissioned officer rank of Ensign in the United States Coast Guard.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ENS Target entity description: ENS is the standard abbreviation for the junior commissioned officer rank of Ensign in the United States Coast Guard.
-
A.
ENS
ENS is a common abbreviation for the École Normale Supérieure, a prestigious French grande école known for its elite training in the sciences and humanities.
-
B.
ENE
ENE was the stock ticker symbol for Enron Corporation, the American energy company infamous for its massive accounting fraud and subsequent 2001 bankruptcy.
-
C.
ENA
ENA is a prestigious French grande école that trained many of the country’s top civil servants and political leaders.
-
D.
ESS
ESS is the commonly used abbreviation for the European Standardization System, the framework through which European standards are developed and harmonized.
-
E.
ESS
ESS is the commonly used abbreviation for Étoile Sportive du Sahel, a prominent multi-sport club based in Sousse, Tunisia, best known for its successful football team.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3455cf4b88190b3c9e93e158a7686 |
completed | April 18, 2026, 8:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0067b0e5708190a286b8a316d6efd2 |
completed | May 10, 2026, 11:10 a.m. |
| NEDg | Description generation | batch_6a006895b8ac8190a8d078e6b9f5bb50 |
completed | May 10, 2026, 11:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00694da4a88190944ae4a70ac9f0c3 |
completed | May 10, 2026, 11:17 a.m. |
Created at: April 10, 2026, 5:15 a.m.