Triple
T256458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooklyn |
E5446
|
entity |
| Predicate | hasBoroughPresident |
P8977
|
FINISHED |
| Object | elected official |
—
|
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: elected official | Statement: [Brooklyn, hasBoroughPresident, elected official]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoroughPresident Context triple: [Brooklyn, hasBoroughPresident, elected official]
-
A.
hasMayor
Indicates that one entity serves as the mayor of another entity, typically a city, town, or municipality.
-
B.
hasBorough
Indicates that one entity is located within, belongs to, or is administratively part of a specific borough.
-
C.
incorporatedAsBorough
Indicates that an entity was formally established and granted legal status as a borough.
-
D.
hasCouncilDistrict
Indicates that an entity is located within or represented by a specific council district.
-
E.
officeHolderMayBe
Indicates that a specified person is permitted or eligible to hold a particular office or position.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d5884c88190a349d7593b688921 |
completed | Feb. 28, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69a25b694c08819085bb4b256fa7736f |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c4b773c81908f1017f40b0bfd07 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.