Triple

T10581083
Position Surface form Disambiguated ID Type / Status
Subject Gov’t Mule E249735 entity
Predicate associatedAct P37 FINISHED
Object Matt Abts E873018 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: Matt Abts | Statement: [Gov’t Mule, associatedAct, Matt Abts]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Abts
Context triple: [Gov’t Mule, associatedAct, Matt Abts]
  • A. Matt Abts chosen
    Matt Abts is an American rock drummer best known for his long-time role in the jam band Gov’t Mule and his powerful, groove-oriented playing style.
  • B. Tod Andrews
    Tod Andrews was an American film, television, and stage actor active in the mid-20th century, known for his character roles across a variety of popular series and movies.
  • C. Dean Fleischer-Camp
    Dean Fleischer-Camp is an American filmmaker and editor best known for co-creating the stop-motion character and film series "Marcel the Shell with Shoes On."
  • D. Lee Zahler
    Lee Zahler was an American film composer and musical director known for scoring numerous serials and B-movies during the 1930s and 1940s.
  • E. Luke Metz
    Luke Metz is a machine learning researcher known for his work on generative models and deep learning, often collaborating with Alec Radford.
  • 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_69d381c9d3d48190a29ee491e1696a0e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5275b2424819093331b3777f12beb completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95e78ad6c81909eaa0cdc41c5cc82 completed April 10, 2026, 8:32 p.m.
Created at: April 6, 2026, 12:38 p.m.