Triple

T9102662
Position Surface form Disambiguated ID Type / Status
Subject Charmed E218395 entity
Predicate setIn P1393 FINISHED
Object San Francisco E242 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: San Francisco | Statement: [Charmed, setIn, San Francisco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Francisco
Context triple: [Charmed, setIn, San Francisco]
  • A. San Francisco
    San Francisco is a coastal neighborhood of the city of Telde in Gran Canaria, Spain, known for its traditional Canarian architecture and historic character.
  • B. San Francisco chosen
    San Francisco is a major coastal city in Northern California known for its hilly landscape, iconic Golden Gate Bridge, and role as a historic center of technology and counterculture.
  • C. San Francisco
    San Francisco is a municipality in Colombia’s Putumayo Department, located in the southwestern part of the country near the Andean and Amazonian regions.
  • D. San Fransokyo
    San Fransokyo is a fictional futuristic hybrid city combining elements of San Francisco and Tokyo, serving as the primary setting of Disney's animated film "Big Hero 6."
  • E. Sausalito
    Sausalito is a picturesque waterfront city in Northern California known for its hillside homes, art galleries, and views of the San Francisco Bay.
  • 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_69ca83db7448819090d0a5de842ef2ac completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc9715d5188190bce68d095e10c2eb completed April 1, 2026, 3:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69d030201a048190a3a1166d23c5ae67 completed April 3, 2026, 9:24 p.m.
Created at: March 30, 2026, 7:15 p.m.