Triple

T8994034
Position Surface form Disambiguated ID Type / Status
Subject Irene Papas E214856 entity
Predicate familyNameAtBirth P18 FINISHED
Object Lelekou E214856 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: Lelekou | Statement: [Irene Papas, familyNameAtBirth, Lelekou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lelekou
Context triple: [Irene Papas, familyNameAtBirth, Lelekou]
  • A. Lelekou chosen
    Lelekou is the birth surname of renowned Greek actress and singer Irene Papas.
  • B. Duékoué
    Duékoué is a town in western Côte d'Ivoire that became notorious as a major site of violence and massacres during the country's civil conflicts.
  • C. Langoué Baï
    Langoué Baï is a renowned forest clearing in Gabon celebrated for its rich biodiversity and frequent gatherings of forest elephants and other wildlife.
  • D. Korandjé
    Korandjé is a highly endangered Northern Songhay language spoken in the oasis town of Tabelbala in southwestern Algeria.
  • E. Nossi-Bé
    Nossi-Bé is an island off the northwest coast of Madagascar known for its tropical beaches, marine biodiversity, and role as a major tourist destination.
  • 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_69ca83a05c608190bdfdbdb25e994b39 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc687798a881908e6fdd9a39219f1d completed April 1, 2026, 12:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb9531748190bd710e0b386b2cbe completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:04 p.m.