Triple
T23117879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of New York municipalities |
E576807
|
entity |
| Predicate | havePowers |
P544
|
FINISHED |
| Object | police power |
—
|
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: police power | Statement: [State of New York municipalities, havePowers, police power]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: havePowers Context triple: [State of New York municipalities, havePowers, police power]
-
A.
hasPower
chosen
Indicates that one entity possesses authority, control, or influence over another entity or over a particular domain or resource.
-
B.
hasSuperpower
Indicates that one entity possesses a special or extraordinary power or ability beyond normal human capabilities.
-
C.
hasNumberOfPowers
Indicates the quantity of distinct powers or abilities that an entity possesses.
-
D.
hasPowerful
Indicates that one entity possesses significant strength, influence, or capability relative to another entity or context.
-
E.
usesPowerFor
Indicates that one entity applies or exploits a particular power, energy, or capability for a specific purpose or activity.
- 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_69e245f6c2e881909a228fdcfeb7c7d3 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e4dd7d8819087cc50b2dc94798e |
completed | April 29, 2026, 4:51 a.m. |
| PD | Predicate disambiguation | batch_69ef89f020588190b43393e048e7eda3 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:59 p.m.