Triple

T13928107
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Chemistry, Technion – Israel Institute of Technology E334913 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: [Faculty of Chemistry, Technion – Israel Institute of Technology, locatedIn, Haifa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haifa
Context triple: [Faculty of Chemistry, Technion – Israel Institute of Technology, 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_69d81c5f739081908bc05b2461f54828 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2aa7e9248190b0523415b9224e2f completed April 14, 2026, 11:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcb6419a3c8190bfaeab65f3909474 completed May 7, 2026, 3:56 p.m.
Created at: April 9, 2026, 10:16 p.m.