Triple

T757452
Position Surface form Disambiguated ID Type / Status
Subject Mount Herzl E15588 entity
Predicate locatedIn P40 FINISHED
Object Jerusalem Forest area E89247 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: Jerusalem Forest area | Statement: [Mount Herzl, locatedIn, Jerusalem Forest area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jerusalem Forest area
Context triple: [Mount Herzl, locatedIn, Jerusalem Forest area]
  • A. Jerusalem Forest chosen
    Jerusalem Forest is a large woodland area on the western outskirts of Jerusalem, known for its hiking trails, scenic viewpoints, and natural respite from the urban environment.
  • B. Kidron Valley
    Kidron Valley is a historic ravine in Jerusalem that runs between the Old City and the Mount of Olives, featuring prominently in biblical tradition and archaeological remains.
  • C. Tel HaShomer
    Tel HaShomer is a neighborhood in Ramat Gan, Israel, best known for its major military base and large government-run hospital complex.
  • D. Mount Herzl
    Mount Herzl is Israel’s national cemetery and a central memorial site in Jerusalem, serving as the burial place of prominent leaders and fallen soldiers.
  • E. Yokneam Illit
    Yokneam Illit is a city in northern Israel known for its high-tech industrial parks and rapid development from a small town into a regional technology hub.
  • 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_69a493599a0081908da65f3407af1ef2 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a66c2e108190a754c60d2eac6676 completed March 1, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a66673d6288190bb6a68c6c376016e completed March 3, 2026, 4:41 a.m.
Created at: March 1, 2026, 7:37 p.m.