Triple

T13525280
Position Surface form Disambiguated ID Type / Status
Subject Art Alexakis E323000 entity
Predicate notableWork P4 FINISHED
Object Santa Monica E163687 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: Santa Monica | Statement: [Art Alexakis, notableWork, Santa Monica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Monica
Context triple: [Art Alexakis, notableWork, 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 small coastal city in southern Mississippi known for its white-sand beaches, proximity to the Gulf of Mexico, and relaxed residential character.
  • E. Long Beach
    Long Beach is a popular, scenic stretch of sandy shoreline on Vietnam’s Phu Quoc Island, known for its sunsets, resorts, and calm tropical waters.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa6ad60819087824e4ac83934ed completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7c6f78e088190a2d241042cfe615f completed May 3, 2026, 10:06 p.m.
Created at: April 9, 2026, 9:44 p.m.