Triple
T17531216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hidalgo County |
E426936
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Palmhurst, 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: Palmhurst, Texas | Statement: [Hidalgo County, contains, Palmhurst, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palmhurst, Texas Context triple: [Hidalgo County, contains, Palmhurst, Texas]
-
A.
Palmhurst, Texas
chosen
Palmhurst, Texas is a small city in Hidalgo County in the Rio Grande Valley region of South Texas, known primarily as a residential community within the McAllen–Edinburg–Mission metropolitan area.
-
B.
Palmview, Texas
Palmview, Texas is a small city in Hidalgo County in the Rio Grande Valley region of South Texas, forming part of the McAllen–Edinburg–Mission metropolitan area.
-
C.
Palmer, Texas
Palmer, Texas is a small town located in Ellis County within the Dallas–Fort Worth metropolitan area.
-
D.
Mount Pleasant, Texas
Mount Pleasant, Texas is a small city in northeastern Texas that serves as a regional commercial and cultural hub within the Ark-La-Tex area.
-
E.
Pampa, Texas
Pampa, Texas is a small city in the Texas Panhandle known historically for its role in the oil and gas industry and as a regional hub for agriculture and transportation.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e453688950819098162d853cd2674e |
completed | April 19, 2026, 4 a.m. |
Created at: April 10, 2026, 5:49 a.m.