Triple
T798321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Island |
E17071
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Huntington |
E39099
|
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: Huntington | Statement: [Long Island, contains, Huntington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huntington Context triple: [Long Island, contains, Huntington]
-
A.
Huntington
chosen
Huntington is a town on the north shore of Long Island in Suffolk County, New York, known for its historic downtown, waterfront, and cultural attractions.
-
B.
Pelham
Pelham is the first name of P. G. Wodehouse, the celebrated English humorist and author known for his Jeeves and Wooster stories.
-
C.
Peabody
Peabody is a suburban city in northeastern Massachusetts known for its location on the North Shore and its historical ties to the leather industry.
-
D.
Avondale
Avondale is a well-known residential and commercial suburb of Harare, Zimbabwe, noted for its shopping centers and relatively affluent character.
-
E.
Canton
Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7b4d9548190aad5fdf1211cf8cd |
completed | March 1, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7b83f0fb4819097f29c9ab90cf1a8 |
completed | March 4, 2026, 4:42 a.m. |
Created at: March 1, 2026, 7:38 p.m.