Triple
T11136303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Dalton |
E263420
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Laredo, Texas, United States |
E121196
|
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: Laredo, Texas, United States | Statement: [Tony Dalton, placeOfBirth, Laredo, Texas, United States]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laredo, Texas, United States Context triple: [Tony Dalton, placeOfBirth, Laredo, Texas, United States]
-
A.
Laredo, Texas
chosen
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.
-
B.
Eagle Pass, Texas
Eagle Pass, Texas is a U.S. border city on the Rio Grande known as a major crossing point and twin city to Piedras Negras, Coahuila, Mexico.
-
C.
Pharr, Texas
Pharr, Texas is a rapidly growing city in the Rio Grande Valley of South Texas, known as a major commercial and transportation hub on the U.S.–Mexico border.
-
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
Laredo is a coastal town in northern Spain’s Cantabria region, known for its long sandy beaches and historic old quarter.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e85daddc8190a1ae2a4a75cc8d50 |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e441fa286881909a8279a8ea6944e7 |
completed | April 19, 2026, 2:46 a.m. |
Created at: April 8, 2026, 9:28 p.m.