Triple

T3554086
Position Surface form Disambiguated ID Type / Status
Subject Palestine E75177 entity
Predicate hasSubregion P285 FINISHED
Object Negev E52188 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: Negev | Statement: [Palestine, hasSubregion, Negev]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Negev
Context triple: [Palestine, hasSubregion, Negev]
  • A. Negev desert chosen
    The Negev desert is a vast arid region in southern Israel known for its stark landscapes, sparse population, and significant historical and strategic importance.
  • B. Judean Desert
    The Judean Desert is a rugged, arid region in eastern Israel and the West Bank, known for its steep canyons, dramatic cliffs, and historical sites overlooking the Dead Sea.
  • C. Tihama
    Tihama is a hot, low-lying coastal plain along the Red Sea, primarily in western Yemen and southwestern Saudi Arabia.
  • D. Nitrian Desert
    The Nitrian Desert is a desert region in northwestern Egypt historically known as a center of early Christian monasticism and ascetic communities.
  • E. Chagai Desert
    The Chagai Desert is an arid region in western Balochistan, Pakistan, known for its harsh landscape and sparse population.
  • 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_69ad85d33c6c819081d5ac1df13b5680 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc05549d88190acdebdd542ea1a67 completed March 8, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38beef8b4819090109ab89e9671d6 completed March 13, 2026, 4 a.m.
Created at: March 8, 2026, 3:20 p.m.