Triple
T1961932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attorney General’s Office (AGO) |
E42605
|
entity |
| Predicate | usesAcronym |
P43
|
FINISHED |
| Object |
AGO
AGO is a common acronym for the Attorney General’s Office, the government body responsible for representing the state in legal matters and providing legal advice to the government.
|
E221777
|
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: AGO | Statement: [Attorney General’s Office (AGO), usesAcronym, AGO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AGO Context triple: [Attorney General’s Office (AGO), usesAcronym, AGO]
-
A.
AGO
AGO is a major art museum in Toronto, Canada, renowned for its extensive collection of Canadian and international art.
-
B.
GA
GA is the official two-letter United States Postal Service abbreviation for the state of Georgia.
-
C.
GA
GA is the commonly used abbreviation for the United Nations General Assembly, the main deliberative body of the UN where all member states are represented.
-
D.
GA
GA is the IATA airline designator for Garuda Indonesia, the national flag carrier of Indonesia.
-
E.
GA
GA is the abbreviation commonly used for Greater Anglia, a train operating company serving routes in East Anglia and London in the United Kingdom.
- 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: AGO Triple: [Attorney General’s Office (AGO), usesAcronym, AGO]
Generated description
AGO is a common acronym for the Attorney General’s Office, the government body responsible for representing the state in legal matters and providing legal advice to the government.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AGO Target entity description: AGO is a common acronym for the Attorney General’s Office, the government body responsible for representing the state in legal matters and providing legal advice to the government.
-
A.
AGO
AGO is a major art museum in Toronto, Canada, renowned for its extensive collection of Canadian and international art.
-
B.
GA
GA is the official two-letter United States Postal Service abbreviation for the state of Georgia.
-
C.
GA
GA is the commonly used abbreviation for the United Nations General Assembly, the main deliberative body of the UN where all member states are represented.
-
D.
GA
GA is the IATA airline designator for Garuda Indonesia, the national flag carrier of Indonesia.
-
E.
GA
GA is the abbreviation commonly used for Greater Anglia, a train operating company serving routes in East Anglia and London in the United Kingdom.
- 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_69a88711151c8190940b2572095059d7 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3aae8c48190afae2cf3af2ae4e9 |
completed | March 7, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae031ef4e48190af93dfd6f33184d3 |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae0386785c8190ae74e5f04a4809fc |
completed | March 8, 2026, 11:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae042728f48190850848116a371794 |
completed | March 8, 2026, 11:20 p.m. |
Created at: March 4, 2026, 7:36 p.m.