Triple
T5986283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohio state courts |
E133233
|
entity |
| Predicate | coversAllCounties |
P19200
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ohio state courts, coversAllCounties, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversAllCounties Context triple: [Ohio state courts, coversAllCounties, true]
-
A.
includesCounty
Indicates that a larger geographic or administrative region contains or encompasses a specific county within its boundaries.
-
B.
hasNumberOfCounties
Indicates the relationship that specifies how many counties are associated with or contained within a given entity.
-
C.
hasAdditionalCounty
Indicates that an entity is associated with one or more counties beyond its primary or originally specified county.
-
D.
hasCentralCounty
Indicates that an administrative or geographic region is associated with a specific county that serves as its central or primary county.
-
E.
regionCoverage
chosen
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049de98648190962b14fd341c93da |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:04 p.m.