Triple

T519149
Position Surface form Disambiguated ID Type / Status
Subject Galilee E10774 entity
Predicate hasPart P35 FINISHED
Object Tiberias E2296 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: Tiberias | Statement: [Galilee, hasPart, Tiberias]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tiberias
Context triple: [Galilee, hasPart, Tiberias]
  • A. Tiberias chosen
    Tiberias is an ancient city in northern Israel on the western shore of the Sea of Galilee, historically significant as a major center of Jewish learning and pilgrimage.
  • B. Ashdod
    Ashdod is a major coastal city in southern Israel that serves as an important cultural and religious hub, including for the Karaite Jewish community.
  • C. Yokneam Illit
    Yokneam Illit is a city in northern Israel known for its high-tech industrial parks and rapid development from a small town into a regional technology hub.
  • D. Capernaum
    Capernaum was an ancient fishing village on the northwestern shore of the Sea of Galilee that became a central setting for Jesus’ ministry in the New Testament.
  • E. Ramla
    Ramla is an Israeli city historically significant as a major religious and communal center for Karaite Jews.
  • 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_69a2e84a0d08819087e01863fcd9abf1 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f19ee6748190916603ef3a9e27f3 completed Feb. 28, 2026, 1:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4b5d50c688190b0093af8870f6fdf completed March 1, 2026, 9:55 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.