Triple
T16240651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cochran County |
E394235
|
entity |
| Predicate | hasLargestCity |
P235
|
FINISHED |
| Object | Morton, 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: Morton, Texas | Statement: [Cochran County, hasLargestCity, Morton, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morton, Texas Context triple: [Cochran County, hasLargestCity, Morton, Texas]
-
A.
Morton, Texas
chosen
Morton, Texas is a small West Texas city that serves as the administrative and economic hub of Cochran County.
-
B.
Morse, Texas
Morse, Texas is a small rural community located in the Texas Panhandle region of the United States.
-
C.
Moody, Texas
Moody, Texas is a small rural city in Central Texas known for its close-knit community and agricultural surroundings.
-
D.
Mason, Texas
Mason, Texas is a small historic town in the Texas Hill Country known for its rural charm and as the birthplace of author Fred Gipson.
-
E.
Muleshoe, Texas
Muleshoe, Texas is a small rural city in Bailey County known for its agricultural economy and its location near the New Mexico border in the Texas Panhandle.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2455e1ce08190b97e2ab3e8c6d535 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:04 a.m.