Triple
T13965288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Paso County, Texas |
E335905
|
entity |
| Predicate | ISOCode |
P208
|
FINISHED |
| Object | US-TX |
E548
|
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: US-TX | Statement: [El Paso County, Texas, ISOCode, US-TX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: US-TX Context triple: [El Paso County, Texas, ISOCode, US-TX]
-
A.
TX
TX is the IATA airline designator assigned to Air Caraïbes, a French Caribbean airline.
-
B.
Texas
chosen
Texas is the second-largest U.S. state by both area and population, known for its diverse landscapes, major cities like Houston and Dallas, and significant cultural and economic influence.
-
C.
The Texas
The Texas is a historic steam locomotive famed for its role in the 1862 Great Locomotive Chase during the American Civil War.
-
D.
Teksas
Teksas is the famously passionate and vocal supporter group of the Turkish football club Bursaspor, known for its intense atmosphere and choreographies at matches.
-
E.
Texas (various locations)
Texas (various locations) refers to multiple places within the U.S. state of Texas where astronaut David R. Scott has lived.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7e24f08190ba939a8044860033 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1d890d48190affd194b2439c271 |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:18 p.m.