Triple
T22351090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UCLA campus |
E552527
|
entity |
| Predicate | nearby |
P350
|
FINISHED |
| Object | Santa Monica |
—
|
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: Santa Monica | Statement: [UCLA campus, nearby, Santa Monica]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Monica Context triple: [UCLA campus, nearby, Santa Monica]
-
A.
Santa Monica
chosen
Santa Monica is a coastal city in western Los Angeles County, California, known for its iconic pier, beaches, and vibrant tourism and entertainment scene.
-
B.
Santa Monica
Santa Monica is a coastal municipality on Siargao Island in the Philippines, known for its laid-back rural atmosphere, beaches, and fishing communities.
-
C.
Long Beach
Long Beach is a coastal city in Southern California known for its busy port, waterfront attractions, and diverse urban community within the Los Angeles metropolitan area.
-
D.
Long Beach
Long Beach is a popular sandy seaside area in Kuşadası, Turkey, known for its long shoreline, swimming, and water sports.
-
E.
Long Beach
Long Beach is a small coastal city in southern Mississippi known for its white-sand beaches, proximity to the Gulf of Mexico, and relaxed residential character.
- 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1579be6d8819088fed70f54ff4e66 |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 16, 2026, 8:44 p.m.