Triple

T15454362
Position Surface form Disambiguated ID Type / Status
Subject La Garde E371729 entity
Predicate nameMeaning P453 FINISHED
Object The Guard E549322 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: The Guard | Statement: [La Garde, nameMeaning, The Guard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Guard
Context triple: [La Garde, nameMeaning, The Guard]
  • A. The Guard
    The Guard is a character portrayed by Frank Morgan, best remembered as the bumbling yet endearing gatekeeper at the Emerald City in the classic film "The Wizard of Oz."
  • B. The Guard chosen
    The Guard is a darkly comedic Irish crime film in which Brendan Gleeson plays an unconventional small-town police officer drawn into an international drug-smuggling investigation.
  • C. A Guarda
    A Guarda is a coastal town in northwestern Spain known for its fishing heritage and the nearby ancient Celtic hillfort of Santa Trega.
  • D. Inner Guard
    The Inner Guard is a Masonic lodge officer responsible for guarding the entrance from within and controlling admission to meetings.
  • E. On Guard
    On Guard is a popular-level Christian apologetics book by philosopher and theologian William Lane Craig that presents arguments for the rationality of the Christian faith.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f131b1481909ff099c3b844ee07 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21b5e1788190bdc8182822f25fa1 completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 3:31 a.m.