Triple
T23228630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Killeen–Temple–Fort Hood region |
E581084
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Temple, 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: Temple, Texas | Statement: [Killeen–Temple–Fort Hood region, majorCity, Temple, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Temple, Texas Context triple: [Killeen–Temple–Fort Hood region, majorCity, Temple, Texas]
-
A.
Temple, Texas
chosen
Temple, Texas is a central Texas city known for its major medical and educational institutions, including significant healthcare and research facilities.
-
B.
Taft, Texas
Taft, Texas is a small city in San Patricio County that functions as part of the greater Corpus Christi metropolitan region in South Texas.
-
C.
Timpson, Texas
Timpson, Texas is a small rural city in East Texas known for its historic railroad roots and tight-knit community.
-
D.
Tenaha, Texas
Tenaha, Texas is a small rural town in East Texas known for its location along major highways and its history within Shelby County.
-
E.
Moody, Texas
Moody, Texas is a small rural city in Central Texas known for its close-knit community and agricultural surroundings.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e246043c48819089bae72c9a9c306c |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f192302e508190b286c284a261f172 |
completed | April 29, 2026, 5:08 a.m. |
Created at: April 17, 2026, 4:09 p.m.