Triple

T1614242
Position Surface form Disambiguated ID Type / Status
Subject Sarah E34678 entity
Predicate traveledTo P2694 FINISHED
Object Gerar E105720 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: Gerar | Statement: [Sarah, traveledTo, Gerar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gerar
Context triple: [Sarah, traveledTo, Gerar]
  • A. Gerar chosen
    Gerar is an ancient Philistine city mentioned in the Hebrew Bible, associated with the patriarchs Abraham and Isaac in the region of the Negev.
  • B. Geneta
    Geneta is a residential district and suburb within Södertälje Municipality in Sweden.
  • C. Ger
    Ger is a prominent Hasidic dynasty, originating in Góra Kalwaria, Poland, known for its large following and significant influence within the Haredi Jewish world.
  • D. Geno
    Geno is the widely used nickname of Hall of Fame University of Connecticut women's basketball coach Geno Auriemma.
  • E. Gweru
    Gweru is a central Zimbabwean city that serves as the capital of the Midlands Province and an important commercial and transportation hub.
  • 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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9098f384c81909ef836ee779466e2 completed March 5, 2026, 4:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51ca2bc48190abb83f4d84782334 completed March 8, 2026, 10:39 a.m.
Created at: March 4, 2026, 7:28 p.m.