Triple

T10284972
Position Surface form Disambiguated ID Type / Status
Subject The Rose Tattoo E241203 entity
Predicate musicBy P1952 FINISHED
Object Alex North E192506 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: Alex North | Statement: [The Rose Tattoo, musicBy, Alex North]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alex North
Context triple: [The Rose Tattoo, musicBy, Alex North]
  • A. Alex North chosen
    Alex North was an American composer renowned for his innovative and influential film scores, including his work on major Hollywood epics and dramas.
  • B. Harold Rome
    Harold Rome was an American composer and lyricist best known for his work on Broadway musicals and film scores in the mid-20th century.
  • C. Christopher Herrmann
    Christopher Herrmann is a hardworking, outspoken firefighter and bar co-owner on the television series "Chicago Fire."
  • D. David Raksin
    David Raksin was an American film composer best known for his influential scores in classic Hollywood cinema, including the iconic music for the film "Laura."
  • E. Bernard Newman
    Bernard Newman was an American costume designer best known for his glamorous work in 1930s Hollywood musicals and films.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2b737788190bfadd0d48ad38f5b completed April 7, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f8444c48819095100c6d1d45ccc7 completed April 9, 2026, 12:52 a.m.
Created at: April 6, 2026, 11:40 a.m.