Triple

T3772919
Position Surface form Disambiguated ID Type / Status
Subject Out of Sight E83237 entity
Predicate editor P1954 FINISHED
Object Anne V. Coates E224130 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: Anne V. Coates | Statement: [Out of Sight, editor, Anne V. Coates]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anne V. Coates
Context triple: [Out of Sight, editor, Anne V. Coates]
  • A. Anne V. Coates chosen
    Anne V. Coates was an acclaimed British film editor best known for her Oscar-winning work on the epic film "Lawrence of Arabia" and her influential decades-long career in cinema.
  • B. Susan V. Booth
    Susan V. Booth is an American theater director and arts leader known for her prominent role as artistic director of major regional theaters, including Chicago’s Goodman Theatre.
  • C. Joan E. Chapman
    Joan E. Chapman is a film editor known for her work on the action movie "First Blood."
  • D. Margaret C. Etter
    Margaret C. Etter was an influential American chemist and crystallographer known for pioneering work in hydrogen bonding and crystal engineering.
  • E. Dolores H. Russ
    Dolores H. Russ was an American philanthropist and co-namesake of the prestigious Fritz J. and Dolores H. Russ Prize in engineering.
  • 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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc57c9e48190a0f254e47348bf32 completed March 8, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589bcbce88190b97b9dcec8a976f4 completed March 14, 2026, 4:15 p.m.
Created at: March 8, 2026, 3:36 p.m.