Triple

T22869007
Position Surface form Disambiguated ID Type / Status
Subject Rachel Auerbach E567133 entity
Predicate placeOfBirth P1 FINISHED
Object Lanivtsi NE NERFINISHED

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: Lanivtsi | Statement: [Rachel Auerbach, placeOfBirth, Lanivtsi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lanivtsi
Context triple: [Rachel Auerbach, placeOfBirth, Lanivtsi]
  • A. Lanivtsi chosen
    Lanivtsi is a small town in western Ukraine known for its location within the historic region of Ternopil in Galicia.
  • B. Loznitsa
    Loznitsa is a small town and municipal center in northeastern Bulgaria known for its agricultural surroundings and local rural character.
  • C. Lypovets
    Lypovets is a town in central Ukraine historically known as a local administrative and trade center.
  • D. Bezhitsa
    Bezhitsa is a district of Bryansk in western Russia, historically known as an industrial town and railway hub.
  • E. Terebovlia
    Terebovlia is a historic town in western Ukraine known for its medieval fortress ruins and role as a regional cultural center.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24589d8348190b96422d13a678bc1 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17f0384a88190a0fbf57b5dca8d5a completed April 29, 2026, 3:46 a.m.
Created at: April 17, 2026, 3:38 p.m.