Triple

T17846657
Position Surface form Disambiguated ID Type / Status
Subject Kfar Saba E445678 entity
Predicate hasSisterCity P919 FINISHED
Object Dimona 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: Dimona | Statement: [Kfar Saba, hasSisterCity, Dimona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dimona
Context triple: [Kfar Saba, hasSisterCity, Dimona]
  • A. Dimona chosen
    Dimona is a town in southern Israel best known for its proximity to the Negev Nuclear Research Center and its role in the development of the Negev desert region.
  • B. Dalila
    Dalila is a biblical figure, often depicted as a Philistine woman who betrays Samson by discovering and revealing the secret of his strength.
  • C. Munise
    Munise is a character from the classic Turkish novel "Çalıkuşu," playing a significant role in the emotional and familial life of the protagonist, Feride.
  • D. Eynat
    Eynat is a feminine given name of Hebrew origin, commonly used in Israel.
  • E. Beyla
    Beyla is a minor figure in Norse mythology, known primarily as a servant of the god Freyr and mentioned briefly in the poem Lokasenna.
  • 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_69d8b9f26f18819089c9e43250bee6ae completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48ffb35248190a80a428686e06d87 completed April 19, 2026, 8:19 a.m.
Created at: April 10, 2026, 10:16 a.m.