Triple

T7643649
Position Surface form Disambiguated ID Type / Status
Subject Simba E173068 entity
Predicate uncle P8496 FINISHED
Object Scar E173069 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: Scar | Statement: [Simba, uncle, Scar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scar
Context triple: [Simba, uncle, Scar]
  • A. Scar chosen
    Scar is the cunning and power-hungry lion antagonist in Disney's animated film "The Lion King," known for plotting to overthrow his brother Mufasa and nephew Simba.
  • B. Scar
    Scar is the ruthless Comanche chief who serves as the primary adversary in the classic Western film "The Searchers."
  • C. Scars
    "Scars" is a soulful, emotionally charged song by British singer-songwriter James Bay that reflects on vulnerability, healing, and the lingering impact of past relationships.
  • D. Scars
    "Scars" is a 2004 rock ballad by Papa Roach that became one of the band’s most commercially successful and recognizable songs, noted for its emotional lyrics about pain and healing.
  • E. Burn
    Burn is a young adult fantasy novel by Patrick Ness that blends dragons, Cold War-era tensions, and themes of prejudice and destiny in a small 1950s American town.
  • 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_69c6995360188190968ee57b72a1627f completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6faef96908190a7724b204f9d8c9e completed March 27, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c870d510f08190ad7706f582e8c1a0 completed March 29, 2026, 12:22 a.m.
Created at: March 27, 2026, 3:58 p.m.