Triple
T31938348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Childress, Texas vicinity |
E815454
|
entity |
| Predicate | countySeatOfSurroundingCounty |
P201656
|
FINISHED |
| Object | Childress, Texas |
—
|
NE NERFINISHED |
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: Childress, Texas | Statement: [Childress, Texas vicinity, countySeatOfSurroundingCounty, Childress, Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countySeatOfSurroundingCounty Context triple: [Childress, Texas vicinity, countySeatOfSurroundingCounty, Childress, Texas]
-
A.
countySeat
Indicates that one place serves as the administrative center or capital of a county.
-
B.
nearestCountySeat
Indicates that one location is the closest county seat geographically to another location.
-
C.
otherCountySeat
Indicates that one entity serves as the county seat of a different county than the one associated with the other entity.
-
D.
containsCountySeat
Indicates that one administrative region or area includes within its boundaries the designated county seat location of a county.
-
E.
hasCountySeatCounty
Indicates that a county seat is administratively associated with and serves as the seat of government for a specific 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_69f348f3035c81908558e2339955abb3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a0010e46d948190a51111b5270fade7 |
completed | May 10, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_6a001061d34c8190bfe73f3d7c061eb7 |
completed | May 10, 2026, 4:58 a.m. |
| PDg | Predicate description generation | batch_6a0010e304a08190a4d0a4fa11a9a3b3 |
completed | May 10, 2026, 5 a.m. |
Created at: May 1, 2026, 12:05 a.m.