Triple
T12992779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GA3 |
E321956
|
entity |
| Predicate | hasRepresentative |
P192
|
FINISHED |
| Object | Drew Ferguson |
E340112
|
NE FINISHED |
How this triple was built (2 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: Drew Ferguson | Statement: [GA3, hasRepresentative, Drew Ferguson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Drew Ferguson Context triple: [GA3, hasRepresentative, Drew Ferguson]
-
A.
Drew Ferguson
chosen
Drew Ferguson is an American Republican politician and dentist serving as a U.S. Representative from Georgia.
-
B.
Drew Brown
Drew Brown is an American musician best known as the guitarist for the pop rock band OneRepublic.
-
C.
Drew Brown
Drew Brown is a writer known for contributing to the publication Good Life.
-
D.
Drew Gordon
Drew Gordon was an American professional basketball player and standout collegiate forward known for his dominant rebounding and interior play, particularly at the University of New Mexico.
-
E.
Drew Bagnell
Drew Bagnell is a roboticist and machine learning researcher known for his work in autonomous systems and his role as a co-founder and chief scientist at Aurora Innovation.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7765788190a9503ef055bc30ca |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d5f4bedc81909b8dfa79a842e12d |
completed | May 3, 2026, 4:58 a.m. |
Created at: April 9, 2026, 8:44 p.m.