Triple

T11272300
Position Surface form Disambiguated ID Type / Status
Subject The Black Crowes E266842 entity
Predicate influencedBy P9 FINISHED
Object Faces E421113 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: Faces | Statement: [The Black Crowes, influencedBy, Faces]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faces
Context triple: [The Black Crowes, influencedBy, Faces]
  • A. Faces
    Faces is a 1968 independent drama film written and directed by John Cassavetes, noted for its raw, improvisational style and intense exploration of marital breakdown and human relationships.
  • B. Faces
    Faces is a critically acclaimed 2014 mixtape by American rapper Mac Miller, known for its introspective lyrics, experimental production, and exploration of themes like addiction and mental health.
  • C. Faces chosen
    Faces was a British rock band formed in 1969, known for its bluesy, hard rock sound and energetic live performances.
  • D. Heads, Features and Faces
    Heads, Features and Faces is an instructional art book by George Bridgman that teaches artists how to construct and draw the human head and facial features with an emphasis on structure and anatomy.
  • E. Azure Face API
    Azure Face API is a cloud-based facial recognition and analysis service from Microsoft that detects, identifies, and analyzes human faces in images.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e965c9048190804ebb48f0a4817b completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f43633948190b86f5603ac50ec47 completed April 19, 2026, 3:26 p.m.
Created at: April 8, 2026, 9:31 p.m.