Triple

T11317565
Position Surface form Disambiguated ID Type / Status
Subject Joseph Stein E268004 entity
Predicate work P12692 FINISHED
Object Mr. Wonderful E246862 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: Mr. Wonderful | Statement: [Joseph Stein, work, Mr. Wonderful]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mr. Wonderful
Context triple: [Joseph Stein, work, Mr. Wonderful]
  • A. Mr. Wonderful chosen
    Mr. Wonderful is a 1993 romantic comedy film about a New York electrician who schemes to find a new husband for his ex-wife so he can afford his dream business.
  • B. Mr. Right
    Mr. Right is a 2015 action-romantic comedy film in which Sam Rockwell plays a eccentric hitman who falls in love while being pursued by his former employers.
  • C. Mr. Jones
    "Mr. Jones" is a hit alternative rock song by Counting Crows, known for its introspective lyrics about fame, dreams, and identity.
  • D. Miss O'Dell
    "Miss O'Dell" is a 1973 George Harrison song, released as the B-side to "Give Me Love (Give Me Peace on Earth)" and inspired by his friend and Apple Records secretary Chris O'Dell.
  • E. Mr. Sparks
    Mr. Sparks is a friendly, mechanically skilled character in the Noddy children's stories who often helps fix things in Toyland.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c3cf748190987838029d9f7fff completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525d3160c8190b58c5c04a66b3e3e completed April 19, 2026, 6:58 p.m.
Created at: April 8, 2026, 9:32 p.m.