Triple
T367718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emerald City |
E7998
|
entity |
| Predicate | contrastsWith |
P278
|
FINISHED |
| Object | The Big Apple |
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: The Big Apple | Statement: [Emerald City, contrastsWith, The Big Apple]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Big Apple Context triple: [Emerald City, contrastsWith, The Big Apple]
-
A.
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.
-
B.
New York City
chosen
New York City is the largest city in the United States, a global center of finance, culture, media, and technology.
-
C.
City of Big Shoulders
City of Big Shoulders is a poetic nickname for Chicago that evokes its history as a powerful industrial and working-class metropolis.
-
D.
Empire State
Empire State is a well-known nickname for the U.S. state of New York, reflecting its historical wealth, influence, and prominence.
-
E.
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.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebeab13c8190b15c2f10310ec6a8 |
completed | Feb. 28, 2026, 1:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4253ec4d48190bdaaf385c9a8e4a9 |
completed | March 1, 2026, 11:38 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.