Triple

T14360944
Position Surface form Disambiguated ID Type / Status
Subject Mayor of Haifa E356096 entity
Predicate seat P75 FINISHED
Object Haifa City Hall E1069792 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 City Hall | Statement: [Mayor of Haifa, seat, Haifa City Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haifa City Hall
Context triple: [Mayor of Haifa, seat, Haifa City Hall]
  • A. Haifa City Hall chosen
    Haifa City Hall is the main municipal government building of Haifa, Israel, serving as the administrative and political center of the city.
  • B. Tel Aviv-Yafo City Hall
    Tel Aviv-Yafo City Hall is the main administrative and governmental building of the city of Tel Aviv-Yafo, housing its municipal offices and leadership.
  • C. Jerusalem City Hall
    Jerusalem City Hall is the main municipal government complex of Jerusalem, housing the offices and chambers of the city’s administration in the historic city center.
  • D. Haifa Auditorium
    Haifa Auditorium is a major cultural venue in Haifa, Israel, hosting concerts, performances, and public events.
  • E. Haifa Hof HaCarmel
    Haifa Hof HaCarmel is a major railway and transportation hub in the southern part of Haifa, Israel, serving as a key gateway between the city and the country’s coastal rail network.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8f54bfb08190a27c0d12731acec2 completed April 14, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c4aba788190bd5ab8cbc772dcf1 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:15 a.m.