Triple
T29580680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYPD 101st Precinct |
E753568
|
entity |
| Predicate | hasPrecinctNumber |
P89932
|
FINISHED |
| Object | 101 |
—
|
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: 101 | Statement: [NYPD 101st Precinct, hasPrecinctNumber, 101]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrecinctNumber Context triple: [NYPD 101st Precinct, hasPrecinctNumber, 101]
-
A.
hasNumberedPrecinct
chosen
Indicates that an entity is associated with a specific precinct identified by a number.
-
B.
partOfPrecinct
Indicates that one entity is a subdivision or component contained within a specific precinct.
-
C.
numberOfPrecincts
Indicates the total count of precincts associated with a given entity or jurisdiction.
-
D.
hasInnerPrecinct
Indicates that one area, structure, or zone contains another, more central or enclosed precinct within its boundaries.
-
E.
hasElectoralDistrictNumber
Indicates that an electoral district is associated with a specific identifying number within an electoral system.
- F. None of above.
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_69f0ef80bf8c8190ad286e99f7df0c63 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69ff84202eb081908ae21a54a4414d68 |
completed | May 9, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69ff833065e4819098579129d4ee17d3 |
completed | May 9, 2026, 6:55 p.m. |
Created at: April 28, 2026, 6:06 p.m.