Triple

T19836331
Position Surface form Disambiguated ID Type / Status
Subject Hanoch Levin E476604 entity
Predicate workLocation P7 FINISHED
Object Tel Aviv NE NERFINISHED

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: Tel Aviv | Statement: [Hanoch Levin, workLocation, Tel Aviv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tel Aviv
Context triple: [Hanoch Levin, workLocation, Tel Aviv]
  • A. Tel Aviv chosen
    Tel Aviv is a major Israeli coastal city known for its vibrant nightlife, high-tech industry, and modernist architecture.
  • B. Netanya
    Netanya is a coastal city in central Israel on the Mediterranean Sea, known for its beaches, tourism, and role as a regional economic center.
  • C. 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.
  • D. Tel Aviv metropolitan area
    The Tel Aviv metropolitan area is Israel’s largest urban and economic hub, centered on the city of Tel Aviv and encompassing numerous surrounding municipalities along the Mediterranean coast.
  • E. Petah Tikva
    Petah Tikva is a major city in central Israel, known as one of the country’s oldest modern Jewish settlements and a significant industrial and commercial hub in the Tel Aviv metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51c7c188190b926f3a2a7b5f881 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e656d275608190841b23de167c401e completed April 20, 2026, 4:39 p.m.
Created at: April 10, 2026, 1:50 p.m.