Triple
T12221214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kettleman City |
E291217
|
entity |
| Predicate | isInCountySeatCity |
P103858
|
FINISHED |
| Object | not a county seat |
—
|
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: not a county seat | Statement: [Kettleman City, isInCountySeatCity, not a county seat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInCountySeatCity Context triple: [Kettleman City, isInCountySeatCity, not a county seat]
-
A.
isInCountySeat
Indicates that one entity (typically a place or facility) is located within the county seat of a given county.
-
B.
isInCountySeatOf
Indicates that one entity is located within the town or city that serves as the administrative center (county seat) of a specified county.
-
C.
isInCountySeatJurisdiction
Indicates that one entity falls under the legal or administrative authority of the county seat associated with another entity.
-
D.
isInCountySeatMetroArea
Indicates that an entity is located within the metropolitan area of a county seat.
-
E.
containsCountySeat
Indicates that one administrative region or area includes within its boundaries the designated county seat location of a county.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d920c3dc9881908c396a4ab34f4836 |
completed | April 10, 2026, 4:09 p.m. |
Created at: April 8, 2026, 9:51 p.m.