Triple
T14465852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Departure |
E358704
|
entity |
| Predicate | locationCity |
P3207
|
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: [Departure, locationCity, New York City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: New York City Context triple: [Departure, locationCity, 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.
NYC
NYC is a historic American railroad company that operated major passenger and freight services across the northeastern and midwestern United States.
-
C.
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.
-
D.
Manhattan
The Manhattan is a classic whiskey-based cocktail, traditionally made with rye or bourbon, sweet vermouth, and bitters, and typically served stirred and garnished with a cherry.
-
E.
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.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91f6d4c08190a12e9a5901ee3508 |
completed | April 14, 2026, 7:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8aa2b7908190831e6c07abcc091d |
completed | May 8, 2026, 7:02 a.m. |
Created at: April 10, 2026, 1:19 a.m.