Triple

T12759281
Position Surface form Disambiguated ID Type / Status
Subject Anthony Veiller E304946 entity
Predicate wrote P2831 FINISHED
Object The Iron Mistress E113602 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 Iron Mistress | Statement: [Anthony Veiller, wrote, The Iron Mistress]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Iron Mistress
Context triple: [Anthony Veiller, wrote, The Iron Mistress]
  • A. The Iron Mistress chosen
    The Iron Mistress is a 1952 historical adventure film about the life of frontiersman Jim Bowie, noted for its swashbuckling action and romantic drama.
  • B. The Age of Steel
    The Age of Steel is a 2006 Doctor Who television episode featuring the Cybermen in an alternate Earth setting, concluding a two-part story that reintroduces the iconic villains to the revived series.
  • C. The Iron Marshal
    The Iron Marshal was the nickname of Louis-Nicolas Davout, one of Napoleon Bonaparte’s most capable and disciplined marshals, renowned for his strict leadership and undefeated battlefield record.
  • D. Men of Iron
    Men of Iron is a historical adventure novel by Howard Pyle that follows the coming-of-age and knighthood of a young squire in 15th-century England.
  • E. Iron Will
    Iron Will is a 1994 Disney adventure film about a young man racing his sled dogs across the wilderness to save his family’s farm.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d8d3eb08190ae998df5cc6d9ba6 completed April 10, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c9c93248190b77c7d229da64ffb completed May 2, 2026, 10:37 p.m.
Created at: April 9, 2026, 5:28 p.m.