Triple

T9907084
Position Surface form Disambiguated ID Type / Status
Subject Resegone E185037 entity
Predicate alsoKnownAs P39 FINISHED
Object Resegun E185037 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: Resegun | Statement: [Resegone, alsoKnownAs, Resegun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Resegun
Context triple: [Resegone, alsoKnownAs, Resegun]
  • A. Resegone chosen
    Resegone is a distinctive serrated mountain massif in the Bergamo Alps of northern Italy, overlooking the city of Lecco and famed for its saw-like ridgeline.
  • B. Resigaro
    Resigaro is an indigenous Arawakan language of the northwestern Amazon, traditionally spoken by a small community in the Peru–Brazil border region and now critically endangered.
  • C. Resuk
    Resuk is an indigenous local language spoken by the community on Atauro Island in Timor-Leste.
  • D. Erakor
    Erakor is a small island and settlement near Efate in Vanuatu, known for its lagoon setting and traditional village life.
  • E. Resita
    Resita is an industrial city in western Romania, historically known for its steel production and heavy machinery manufacturing.
  • 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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb50ec61481908f42bd2aa55d9a6e completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1eb346c7081908300e54cd639b027 completed April 5, 2026, 4:55 a.m.
Created at: March 30, 2026, 8:41 p.m.