Triple
T10081948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairfield University |
E213921
|
entity |
| Predicate | cityServed |
P82
|
FINISHED |
| Object | Fairfield |
E659759
|
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: Fairfield | Statement: [Fairfield University, cityServed, Fairfield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fairfield Context triple: [Fairfield University, cityServed, Fairfield]
-
A.
Fairfield
Fairfield is the middle name of John F. Dryden, the American businessman and politician who founded the Prudential Insurance Company of America.
-
B.
Fairfield
Fairfield is a midsized city in Northern California that serves as the county seat of Solano County and lies between San Francisco and Sacramento in the greater Bay Area region.
-
C.
Fairfield
Fairfield is a small settlement located within the High Peak area of Derbyshire in England.
-
D.
Fairfield
Fairfield is a prominent mountain in England's Lake District, known for its high plateau summit and popular horseshoe ridge walk offering extensive views.
-
E.
Fairfield
chosen
Fairfield is a town in the United States state of Connecticut, known for its affluent suburban character and coastal location along Long Island Sound.
- 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd03482d481908b03d35dc2d16395 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b66b256c8190861066f7c19008d2 |
completed | April 5, 2026, 7:22 p.m. |
Created at: March 30, 2026, 9 p.m.