Triple
T32784782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. metropolitan areas |
E838463
|
entity |
| Predicate | includeExamples |
P100896
|
FINISHED |
| Object | New York metropolitan area |
E7505
|
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 metropolitan area | Statement: [U.S. metropolitan areas, includeExamples, New York metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includeExamples Context triple: [U.S. metropolitan areas, includeExamples, New York metropolitan area]
-
A.
includesExamplesSuchAs
chosen
Indicates that one entity provides specific instances or samples that illustrate or clarify another entity.
-
B.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
C.
includesSee
Indicates that one entity’s scope, content, or experience contains or encompasses the act of seeing or visual perception involving another entity.
-
D.
includesShow
Indicates that one entity contains or features a particular show as part of its content or offerings.
-
E.
includedWith
Indicates that one entity is provided or packaged together as part of another entity.
- F. None of above.
Provenance (4 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_69f3493b83f48190be335cd42465cecf |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0205c0bff481908238a382459b3a93 |
completed | May 11, 2026, 4:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34b1666e34819094889e084aa6d951 |
completed | June 19, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_6a0205143f20819087ee31576835be26 |
completed | May 11, 2026, 4:34 p.m. |
Created at: May 1, 2026, 1:14 a.m.