Triple

T16457573
Position Surface form Disambiguated ID Type / Status
Subject 50/50 E399720 entity
Predicate starring P1507 FINISHED
Object Andrew Airlie E1027897 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: Andrew Airlie | Statement: [50/50, starring, Andrew Airlie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andrew Airlie
Context triple: [50/50, starring, Andrew Airlie]
  • A. Andrew Airlie chosen
    Andrew Airlie is a Canadian actor known for his work in film and television, including roles in series like "Reaper" and the "Fifty Shades" film franchise.
  • B. Daniel Ralls
    Daniel Ralls was an early 19th-century Missouri legislator and local political figure after whom Ralls County, Missouri, is named.
  • C. Bruce Davey
    Bruce Davey is an Australian film producer best known for his long-time collaboration with Mel Gibson and for co-founding the production company Icon Productions.
  • D. Andy Hertzfeld
    Andy Hertzfeld is a pioneering software engineer best known as a key member of the original Apple Macintosh development team and a co-creator of the Mac’s graphical user interface.
  • E. Andrew Tridgell
    Andrew Tridgell is an Australian computer programmer best known for creating the Samba software suite and contributing extensively to free and open-source software.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d7ef5cc819084cfeb1a3e39d3cc completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f51d93081909ede0adcf8e604d4 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:10 a.m.