Triple

T14785460
Position Surface form Disambiguated ID Type / Status
Subject Martín (Hache) E347511 entity
Predicate title P38 FINISHED
Object Martín (Hache) E347511 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: Martín (Hache) | Statement: [Martín (Hache), title, Martín (Hache)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martín (Hache)
Context triple: [Martín (Hache), title, Martín (Hache)]
  • A. Martín (Hache) chosen
    Martín (Hache) is a 1997 Argentine-Spanish drama film that explores generational conflict, identity, and disillusionment through the strained relationship between a troubled young man and his estranged father in Madrid.
  • B. Martín
    Martín is a masculine given name of Latin origin, commonly used in Spanish-speaking countries and derived from the name Martinus, associated with the Roman god Mars.
  • C. Herrero
    Herrero is a Spanish occupational surname derived from the word for "blacksmith" or "smith."
  • D. Martínez
    Martínez is a common Spanish-language surname widely borne across Spain and Latin America.
  • E. De Herrera
    De Herrera is a Spanish surname, often associated with noble lineages and historical figures from Spain and Latin America.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deca9f1c9c8190a8b28ba0ddd3e2e3 completed April 14, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24b816388190be1127fe34a58d1d completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:31 a.m.