Triple
T22907660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rocky Point |
E568494
|
entity |
| Predicate | officialName |
P66
|
FINISHED |
| Object | Puerto Peñasco |
—
|
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: Puerto Peñasco | Statement: [Rocky Point, officialName, Puerto Peñasco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Puerto Peñasco Context triple: [Rocky Point, officialName, Puerto Peñasco]
-
A.
Puerto Peñasco
chosen
Puerto Peñasco is a Mexican resort city on the Gulf of California, popular for its beaches and tourism, especially among visitors from the nearby U.S. Southwest.
-
B.
Nogales
Nogales is a Chilean municipality located in the Province of Quillota in the Valparaíso Region.
-
C.
Nogales
Nogales is a municipality and town in the state of Veracruz, Mexico, known for its mountainous terrain and role as part of the Orizaba metropolitan area.
-
D.
Nogales
Nogales is a small municipality in the Tierra de Barros comarca of the province of Badajoz, in the autonomous community of Extremadura, Spain.
-
E.
Acaponeta
Acaponeta is a town and municipality in the Mexican state of Nayarit, known for its agricultural economy and location near the Acaponeta River.
- 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_69e2458cd9e48190943ad2e34485d939 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18071b9ec81908922d5f046f7930a |
completed | April 29, 2026, 3:52 a.m. |
Created at: April 17, 2026, 3:42 p.m.