Triple
T9960162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coronado Beach |
E195546
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Coronado |
E148166
|
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: Coronado | Statement: [Coronado Beach, locatedIn, Coronado]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coronado Context triple: [Coronado Beach, locatedIn, Coronado]
-
A.
Coronado
chosen
Coronado is a resort city on a peninsula in Southern California known for its historic Hotel del Coronado, beaches, and proximity to downtown San Diego.
-
B.
Coronado
Coronado is a summit of the Pichu Pichu volcanic massif in southern Peru, forming part of the Andean mountain range.
-
C.
Calipatria
Calipatria is a small city in Southern California’s Imperial Valley known for its agricultural economy and notably low elevation below sea level.
-
D.
San Quintín
San Quintín is a coastal town in Baja California, Mexico, known for its agricultural production, volcanic landscapes, and growing tourism along the Pacific coast.
-
E.
Carlsbad
Carlsbad is a coastal city in northern San Diego County, California, known for its beaches, family attractions like LEGOLAND California, and affluent residential communities.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb6d08fdc8190a77b9c97830035bc |
completed | April 2, 2026, 12:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23d867b408190ab630ae4af0fb827 |
completed | April 5, 2026, 10:46 a.m. |
Created at: March 30, 2026, 8:46 p.m.