Triple
T15749030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCTD |
E381798
|
entity |
| Predicate | serviceArea |
P82
|
FINISHED |
| Object | Del Mar, California |
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, California | Statement: [NCTD, serviceArea, Del Mar, California]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Del Mar, California Context triple: [NCTD, serviceArea, Del Mar, California]
-
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.
Dana Point, California
Dana Point, California is a coastal city in southern Orange County known for its scenic harbor, beaches, and surfing.
-
C.
Del Mar City Beach
Del Mar City Beach is a popular Southern California coastal destination known for its wide sandy shoreline, scenic bluffs, and relaxed small-town atmosphere.
-
D.
Solana Beach
Solana Beach is a small coastal city in Southern California known for its beaches, arts scene, and relaxed seaside atmosphere.
-
E.
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.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0502fd3608190b42e647b9c2b41a1 |
completed | April 16, 2026, 2:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff830b85408190b9ae4d6752524b99 |
completed | May 9, 2026, 6:55 p.m. |
Created at: April 10, 2026, 4:46 a.m.