Triple
T9511553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newport Coast, California |
E229408
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Orange Coast |
E210670
|
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: Orange Coast | Statement: [Newport Coast, California, region, Orange Coast]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orange Coast Context triple: [Newport Coast, California, region, Orange Coast]
-
A.
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.
-
B.
Oceanside
Oceanside is a suburban hamlet in Nassau County, Long Island, New York, known as a residential community near the South Shore waterfront.
-
C.
Orange Coast region
chosen
The Orange Coast region is a coastal area of Orange County, California, encompassing cities like Santa Ana and neighboring communities along or near the Pacific shoreline.
-
D.
South Bay
South Bay is a coastal region in southwestern Los Angeles County known for its beach cities, aerospace industry presence, and suburban communities.
-
E.
South Bay
South Bay is the southern region of the San Francisco Bay Area, known for encompassing much of Silicon Valley and several major tech-centric cities.
- 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_69ca84777560819084cddd999badc1aa |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98699b788190b1a475e1b1883584 |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a37c7ec8190a24ae0eec76b4f67 |
completed | April 4, 2026, 4:20 p.m. |
Created at: March 30, 2026, 7:58 p.m.