Triple

T12715964
Position Surface form Disambiguated ID Type / Status
Subject Isfiya E303839 entity
Predicate locatedOn P40 FINISHED
Object Mount Carmel E69227 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: Mount Carmel | Statement: [Isfiya, locatedOn, Mount Carmel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Carmel
Context triple: [Isfiya, locatedOn, Mount Carmel]
  • A. Mount Carmel chosen
    Mount Carmel is a coastal mountain range in northern Israel known for its religious significance, scenic landscapes, and the city of Haifa built on its slopes.
  • B. Mount Carmel
    Mount Carmel is a residential neighborhood in Hamden, Connecticut, known for its proximity to Sleeping Giant State Park and Quinnipiac University.
  • C. Mount Tabor
    Mount Tabor is a prominent hill in northern Israel venerated in Christian tradition as the site of Jesus’ Transfiguration and a longstanding place of pilgrimage.
  • D. Mount Meron
    Mount Meron is a prominent mountain in northern Israel known for its religious significance, nature reserves, and status as one of the country's highest peaks.
  • E. Mount Zion
    Mount Zion is a San Francisco medical campus and hospital complex associated with the University of California, San Francisco, known for providing specialized clinical care and research.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9620bd6148190a2f50067a4c18c14 completed April 10, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671bad5108190915d14c3ec3d2e27 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:23 p.m.