Triple
T36581938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richmond County |
E902418
|
entity |
| Predicate | geographicRankAmongNYCBoroughs |
P192526
|
FINISHED |
| Object | third-largest in area |
—
|
LITERAL 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: third-largest in area | Statement: [Richmond County, geographicRankAmongNYCBoroughs, third-largest in area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicRankAmongNYCBoroughs Context triple: [Richmond County, geographicRankAmongNYCBoroughs, third-largest in area]
-
A.
rankByPopulationInNYC
Indicates the relative ordering of entities based on the size of their populations within New York City.
-
B.
positionInBorough
Indicates that one entity is located within or belongs to the geographic area of a specific borough.
-
C.
locatedInBoroughCommunityDistrict
Indicates that something is situated within a specific borough community district.
-
D.
haveMostDenselyPopulatedBorough
Indicates that one entity possesses the borough with the highest population density compared to other boroughs in a given context.
-
E.
isBoroughSeatOf
Indicates that a place serves as the administrative center or seat of government for a specific borough.
- F. None of above. chosen
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_69f76e64d8908190868473959a250b94 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69fd0d0aebac8190868a7714ddb4f1fd |
completed | May 7, 2026, 10:07 p.m. |
Created at: May 3, 2026, 4:11 p.m.