Triple
T12025413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monahans |
E286261
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Odessa, Texas |
E251869
|
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: Odessa, Texas | Statement: [Monahans, hasNearbyCity, Odessa, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Odessa, Texas Context triple: [Monahans, hasNearbyCity, Odessa, Texas]
-
A.
Odessa, Texas
chosen
Odessa, Texas is a mid-sized West Texas city known for its oil and gas industry, high school football culture, and role as a regional economic hub in the Permian Basin.
-
B.
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.
-
C.
O'Donnell, Texas
O'Donnell, Texas is a small rural community in West Texas known historically for its agricultural roots and tight-knit local population.
-
D.
Columbus, Texas
Columbus, Texas is a small historic city in southeastern Texas that serves as the county seat of Colorado County and lies west of the greater Houston metropolitan region.
-
E.
Dublin, Texas
Dublin, Texas is a small city in north-central Texas known historically for its dairy industry and as a former longtime bottler of Dr Pepper made with cane sugar.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903f02638819091e0cc0e93fa5ea7 |
completed | April 10, 2026, 2:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e3af3cc8190b2a0e3531713aca5 |
completed | May 2, 2026, 3:54 p.m. |
Created at: April 8, 2026, 9:47 p.m.