Triple

T519151
Position Surface form Disambiguated ID Type / Status
Subject Galilee E10774 entity
Predicate hasPart P35 FINISHED
Object Safed E4532 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: Safed | Statement: [Galilee, hasPart, Safed]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Safed
Context triple: [Galilee, hasPart, Safed]
  • A. Safed chosen
    Safed is a historic hilltop city in northern Israel renowned as one of Judaism’s four holy cities and a major center of Jewish mysticism (Kabbalah).
  • B. Bat Yam
    Bat Yam is a coastal city in central Israel, located just south of Tel Aviv along the Mediterranean Sea.
  • 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. Herzliya
    Herzliya is a coastal city in central Israel known as a high-tech and academic hub, home to major technology companies and institutions.
  • E. Jaffa
    Jaffa is an ancient port city on the Mediterranean coast, now part of Tel Aviv-Yafo in Israel, known for its historic harbor, mixed Arab-Jewish population, and continuous habitation since antiquity.
  • 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_69a4e0277eb08190984ff5bcb9f349a0 completed March 2, 2026, 12:56 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.