Triple
T12759110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veronica Escobar |
E304941
|
entity |
| Predicate | work location |
P1527
|
FINISHED |
| Object | El Paso, Texas |
E16599
|
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: El Paso, Texas | Statement: [Veronica Escobar, work location, El Paso, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: El Paso, Texas Context triple: [Veronica Escobar, work location, El Paso, Texas]
-
A.
El Paso
chosen
El Paso is a large border city in far western Texas known for its strong cultural ties with Mexico and its role as a major economic and transportation hub in the region.
-
B.
El Paso
El Paso is a municipality on the Spanish island of La Palma in the Canary Islands, known for its volcanic landscapes and proximity to the Cumbre Vieja ridge.
-
C.
Laredo
Laredo is a coastal town in northern Spain’s Cantabria region, known for its long sandy beaches and historic old quarter.
-
D.
Laredo
Laredo is a base-level trim of the Jeep Grand Cherokee SUV, offering essential features at a more affordable price point.
-
E.
Laredo, Texas
Laredo, Texas is a major city on the U.S.–Mexico border and a key international trade hub located along the Rio Grande in southern Texas.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8d3eb08190ae998df5cc6d9ba6 |
completed | April 10, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b8a79488190aaf95d4f2e20a7bc |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:28 p.m.