Triple
T4888671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Diego metropolitan area |
E109503
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Del Mar |
E123564
|
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: Del Mar | Statement: [San Diego metropolitan area, hasCity, Del Mar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Del Mar Context triple: [San Diego metropolitan area, hasCity, Del Mar]
-
A.
Del Mar
chosen
Del Mar is a coastal city in San Diego County, California, known for its beaches, upscale residential areas, and the Del Mar Fairgrounds and racetrack.
-
B.
Oceanside
Oceanside is a coastal city in northern San Diego County known for its beaches, historic wooden pier, and laid-back Southern California surf culture.
-
C.
Santa Anita
Santa Anita is a Mexico City Metro station that serves as a transfer point between Line 4 and Line 8 in the southeastern part of the city.
-
D.
Del Mar station
Del Mar station is a light rail station in Pasadena, California, serving the Los Angeles Metro A Line and providing access to the Old Pasadena district.
-
E.
Solana Beach
Solana Beach is a small coastal city in Southern California known for its beaches, arts scene, and relaxed seaside atmosphere.
- 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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e053db8819087828e753c78d341 |
completed | March 20, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be681704f08190938aec498d7d4662 |
completed | March 21, 2026, 9:42 a.m. |
Created at: March 20, 2026, 1:28 p.m.