Triple
T1211262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Adjustment Bureau |
E26003
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object | New York City |
E40
|
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: New York City | Statement: [The Adjustment Bureau, setting, New York City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: New York City Context triple: [The Adjustment Bureau, setting, New York City]
-
A.
New York City
chosen
New York City is the largest city in the United States, a global center of finance, culture, media, and technology.
-
B.
New York
New York is a populous and economically significant U.S. state known for New York City, a global center of finance, culture, and media.
-
C.
Manhattan
Manhattan is the densely populated, iconic core borough of New York City, known for its skyscrapers, cultural institutions, and role as a global financial and media center.
-
D.
Brooklyn
Brooklyn is a populous and culturally diverse borough of New York City known for its distinct neighborhoods, arts scene, and iconic landmarks like the Brooklyn Bridge.
-
E.
Washington, New York
Washington, New York is a rural town in Dutchess County known for its historic hamlet of Millbrook, scenic landscapes, and equestrian and agricultural heritage.
- 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_69a4948331fc8190b531ac9bec71c491 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bde581308190bbe30683bf6c48c3 |
completed | March 1, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfb7447408190a63a1e21b087dbf8 |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 1, 2026, 7:46 p.m.