Triple

T2267997
Position Surface form Disambiguated ID Type / Status
Subject Tom Hollander E50191 entity
Predicate notableWork P4 FINISHED
Object About Time E36276 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: About Time | Statement: [Tom Hollander, notableWork, About Time]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: About Time
Context triple: [Tom Hollander, notableWork, About Time]
  • A. About Time chosen
    About Time is a 2013 British romantic comedy-drama film written and directed by Richard Curtis that blends time travel with a heartfelt story about love and family.
  • B. Kind dieser Zeit
    Kind dieser Zeit is an autobiographical novel by Klaus Mann that portrays the disillusionment and political radicalization of German youth during the rise of Nazism.
  • C. In Time
    In Time is a 2011 science-fiction thriller film set in a future where time is used as currency, starring Justin Timberlake and Amanda Seyfried.
  • D. For the Time Being
    For the Time Being is a long Christmas-themed poem by W. H. Auden that blends religious reflection with modern existential concerns.
  • E. Nick of Time
    "Nick of Time" is a classic episode of the original The Twilight Zone series in which a superstitious man becomes obsessed with a fortune-telling machine in a small-town diner.
  • 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_69a88b01e0048190ba96431b5f990ba9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1bbb49c8190822c7d809375e879 completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71d70e488190a2f8276dd7a7bf9e completed March 9, 2026, 7:08 a.m.
Created at: March 4, 2026, 7:48 p.m.