Triple

T11955189
Position Surface form Disambiguated ID Type / Status
Subject Martin Jarmond E284532 entity
Predicate givenName P17 FINISHED
Object Martin E223140 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: Martin | Statement: [Martin Jarmond, givenName, Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martin
Context triple: [Martin Jarmond, givenName, Martin]
  • A. Martin
    Martin is a minor but kind-hearted character in Ernest Hemingway's novella "The Old Man and the Sea," known for helping the old fisherman Santiago.
  • B. Martin chosen
    Martin is a masculine given name of Latin origin, commonly used in many European languages.
  • C. Martin
    Martin is a character in Don DeLillo’s novel "Falling Man," which explores the personal and psychological aftermath of the September 11 attacks.
  • D. Martin
    Martin is a 1978 American horror film directed by George A. Romero that blends psychological drama and vampire mythology in a gritty, realistic style.
  • E. Martin
    Martin is the middle name of Henry Martin Tupper, an individual likely known in historical or biographical records.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90366fda8819083168c93abad27d4 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f459175f808190974ac70431f35c74 completed May 1, 2026, 7:41 a.m.
Created at: April 8, 2026, 9:45 p.m.