Triple
T15332802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palestine Municipal Airport |
E366580
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Palestine, Texas |
E366567
|
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: Palestine, Texas | Statement: [Palestine Municipal Airport, locatedIn, Palestine, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palestine, Texas Context triple: [Palestine Municipal Airport, locatedIn, Palestine, Texas]
-
A.
Palestine, Texas
chosen
Palestine, Texas is a small East Texas city known for its historic downtown, dogwood blossoms, and role as a regional rail and commerce hub.
-
B.
Turkey, Texas
Turkey, Texas is a small rural community in the Texas Panhandle best known as the hometown of Western swing music legend Bob Wills.
-
C.
Hannibal, Texas
Hannibal, Texas is a small rural unincorporated community located in Erath County in north-central Texas.
-
D.
Joshua, Texas
Joshua, Texas is a small city in north-central Texas that forms part of the Dallas–Fort Worth metropolitan area.
-
E.
Navasota, Texas
Navasota, Texas is a small city in Grimes County that serves as a historic railroad and commercial hub within the Greater Houston metropolitan area.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0268608190947a58f559a67717 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a67adf88190bbe15040761d235e |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:17 a.m.