Triple

T1215678
Position Surface form Disambiguated ID Type / Status
Subject Hasidism E26100 entity
Predicate hasDemographicCenter P25074 FINISHED
Object Bnei Brak E102846 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: Bnei Brak | Statement: [Hasidism, hasDemographicCenter, Bnei Brak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bnei Brak
Context triple: [Hasidism, hasDemographicCenter, Bnei Brak]
  • A. Bnei Brak chosen
    Bnei Brak is a densely populated city in Israel known as a major center of ultra-Orthodox Jewish life and culture.
  • B. Herzliya
    Herzliya is a coastal city in central Israel known as a high-tech and academic hub, home to major technology companies and institutions.
  • C. Keren Hayesod
    Keren Hayesod is a central fundraising organization for Israel and the Jewish people worldwide, supporting immigration, settlement, and social development projects in partnership with major Zionist institutions.
  • D. Ramat Gan
    Ramat Gan is a city in the Tel Aviv District of Israel, known for its diamond exchange district, business centers, and large urban park.
  • E. Rehovot
    Rehovot is a city in central Israel known for its scientific and agricultural research institutions, including the Weizmann Institute of Science.
  • 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_69a4948331fc8190b531ac9bec71c491 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf169868819090cfab7e34c40c67 completed March 1, 2026, 10:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac831fb6bc8190907f36e52489ec5c completed March 7, 2026, 7:57 p.m.
Created at: March 1, 2026, 7:46 p.m.