Triple
T1552499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tammany Hall |
E33123
|
entity |
| Predicate | controlledOffice |
P31164
|
FINISHED |
| Object | Mayor of New York City |
—
|
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: Mayor of New York City | Statement: [Tammany Hall, controlledOffice, Mayor of New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controlledOffice Context triple: [Tammany Hall, controlledOffice, Mayor of New York City]
-
A.
includedOffice
Indicates that one office is contained within, or forms part of, another office or organizational unit.
-
B.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
-
C.
limitsOffice
Indicates that one entity imposes a restriction or cap on the scope, duration, or powers of another entity’s office or official position.
-
D.
usedByOffice
Indicates that something is utilized, operated, or employed by an office or office-related entity.
-
E.
inOfficeDuring
Indicates that an entity holds or occupies an office or position throughout a specified time period.
- 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_69a885ee6db8819099502bc5ce8af881 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa574094048190a2d7fc3ac904d51e |
completed | March 6, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69a907b426dc8190975c024a50955368 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69aa573ee8e0819084abf59f1ddbd1da |
completed | March 6, 2026, 4:25 a.m. |
Created at: March 4, 2026, 7:26 p.m.