Triple
T14969435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hockley County |
E373277
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Levelland, Texas |
E1036262
|
NE 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: Levelland, Texas | Statement: [Hockley County, seat, Levelland, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Levelland, Texas Context triple: [Hockley County, seat, Levelland, Texas]
-
A.
Levelland, Texas
chosen
Levelland, Texas is a small city in Hockley County known for its agricultural economy, proximity to Lubbock, and a famous 1957 UFO sighting.
-
B.
Weatherford, Texas
Weatherford, Texas is a historic North Texas city in the Dallas–Fort Worth metropolitan area known for its Western heritage, peach industry, and small-town charm.
-
C.
Leonard, Texas
Leonard, Texas is a small rural city in North Texas known for its tight-knit community and annual Leonard Picnic celebration.
-
D.
Llano, Texas
Llano, Texas is a small historic city in the Texas Hill Country known for its scenic river setting, granite outcrops, and role as the county seat of Llano County.
-
E.
Millican, Texas
Millican, Texas is a small rural community in east-central Texas known for its historic role as an early railroad town.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e44cb0819096e09f8026ef8174 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8be4b0a88190989022108a58370d |
completed | May 9, 2026, 1:20 a.m. |
Created at: April 10, 2026, 2:49 a.m.