Triple

T3196457
Position Surface form Disambiguated ID Type / Status
Subject Haifa Center HaShmona railway station E66946 entity
Predicate locatedIn P40 FINISHED
Object Haifa E12305 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: Haifa | Statement: [Haifa Center HaShmona railway station, locatedIn, Haifa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haifa
Context triple: [Haifa Center HaShmona railway station, locatedIn, Haifa]
  • A. Haifa chosen
    Haifa is a major Israeli city on the Mediterranean coast, known for its significant port, mixed Jewish-Arab population, and the terraced Baháʼí Gardens on Mount Carmel.
  • 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. Ramla
    Ramla is an Israeli city historically significant as a major religious and communal center for Karaite Jews.
  • D. Tel Aviv
    Tel Aviv is a major Israeli coastal city known for its vibrant nightlife, high-tech industry, and modernist architecture.
  • E. Eilat
    Eilat is Israel’s southernmost city and a major Red Sea resort and port known for its beaches, coral reefs, and tourism.
  • 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_69ad8588ba18819086a10951c32ecb80 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada7177b488190b7a1b40ff3fae15f completed March 8, 2026, 4:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3601894819082568a7ee8d6aabc completed March 14, 2026, 2:09 a.m.
Created at: March 8, 2026, 3:07 p.m.