Triple

T8366201
Position Surface form Disambiguated ID Type / Status
Subject Sasun region E197131 entity
Predicate associatedWithHero P2830 FINISHED
Object Little Mher E193089 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: Little Mher | Statement: [Sasun region, associatedWithHero, Little Mher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Little Mher
Context triple: [Sasun region, associatedWithHero, Little Mher]
  • A. Little Mher chosen
    Little Mher is a heroic figure from the Armenian epic cycle "Daredevils of Sassoun," known as a mighty warrior and the son of the legendary hero David of Sassoun.
  • B. Meireles
    Meireles is a Brazilian surname most prominently associated with Cildo Meireles, a leading contemporary conceptual artist known for his politically charged installations and interventions.
  • C. Tebbe
    Tebbe is a German surname that serves as the etymological root for the name Tibbets.
  • D. Lila
    Lila is a novel by Marilynne Robinson that continues her acclaimed Gilead series, exploring themes of grace, poverty, and belonging through the life of its enigmatic title character.
  • E. Lila
    Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
  • 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_69ca82f2dbe48190aba982e75a0d94de completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb808cf80c8190941c3cc0248a5df2 completed March 31, 2026, 8:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde7c747b48190b1979b4eaf281df5 completed April 2, 2026, 3:51 a.m.
Created at: March 30, 2026, 6 p.m.