Triple

T22541219
Position Surface form Disambiguated ID Type / Status
Subject Must Love Dogs E557292 entity
Predicate musicBy P1952 FINISHED
Object Craig Armstrong NE NERFINISHED

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: Craig Armstrong | Statement: [Must Love Dogs, musicBy, Craig Armstrong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Craig Armstrong
Context triple: [Must Love Dogs, musicBy, Craig Armstrong]
  • A. Craig Armstrong chosen
    Craig Armstrong is a Scottish composer and arranger renowned for his emotive film scores and orchestral works, including music for major films such as "Love Actually," "Moulin Rouge!" and "The Great Gatsby."
  • B. Craig Armstrong
    Craig Armstrong is a television producer best known for his work as an executive producer on popular reality and home-renovation series.
  • C. Scot Armstrong
    Scot Armstrong is an American screenwriter and producer known for his work on hit comedy films such as "Old School," "Road Trip," and "The Hangover Part II."
  • D. Kevin Armstrong
    Kevin Armstrong is a British guitarist and producer best known for his session and touring work with artists such as David Bowie and Iggy Pop.
  • E. David Armstrong
    David Armstrong is a relatively common personal name shared by various individuals across fields such as sports, academia, and the arts.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e58662081909ae346ab384514ca completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15f3251808190a72b849157854d8d completed April 29, 2026, 1:30 a.m.
Created at: April 16, 2026, 8:51 p.m.