Triple

T13499363
Position Surface form Disambiguated ID Type / Status
Subject Janet Munro E320843 entity
Predicate workedOn P3 FINISHED
Object Sebastian E883692 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: Sebastian | Statement: [Janet Munro, workedOn, Sebastian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sebastian
Context triple: [Janet Munro, workedOn, Sebastian]
  • A. Sebastian
    Sebastian is a masculine given name of Latin origin, commonly used in many European and English-speaking countries.
  • B. Sebastian
    Sebastian is a small coastal city in eastern Florida known for its riverfront location, access to the Indian River Lagoon, and proximity to the Sebastian Inlet and Atlantic beaches.
  • C. Sebastian James
    Sebastian James is a British business executive best known for serving as the chief executive officer of Boots UK.
  • D. Sebastian Rick
    Sebastian Rick is a German local politician serving as the mayor of the town of Naunhof in Saxony.
  • E. Sebastian Graves chosen
    Sebastian Graves is a highly skilled but uptight British MI6 agent whose life is upended when he is reunited with his crude, long-lost brother in the action-comedy film "The Brothers Grimsby."
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf4fab688190bdc746985b0c7338 completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75487cb3c8190ab7f3bc36755b74c completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:43 p.m.