Triple
T30041417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Settlement Police Department |
E763313
|
entity |
| Predicate | hasJurisdictionAreaType |
P6822
|
FINISHED |
| Object | urban 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: urban area | Statement: [White Settlement Police Department, hasJurisdictionAreaType, urban area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJurisdictionAreaType Context triple: [White Settlement Police Department, hasJurisdictionAreaType, urban area]
-
A.
usesJurisdictionType
Indicates that one entity applies, operates under, or is governed by a particular type or category of jurisdiction.
-
B.
includesJurisdictionType
Indicates that a given entity’s authority, scope, or coverage extends to and encompasses a specified type of jurisdiction.
-
C.
hasJurisidiction
Indicates that one entity holds legal authority or control over another entity, area, or matter.
-
D.
hasJurisdictionCharacteristic
Indicates that a jurisdiction possesses a particular legal, regulatory, or administrative characteristic.
-
E.
hasAreaType
chosen
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
- 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_69f22470a89c8190be7273297c0e0d19 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f679d92a288190bf4731c3c73a3d57 |
completed | May 2, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 6:53 p.m.