Triple

T13307155
Position Surface form Disambiguated ID Type / Status
Subject Gharb Sohail E316964 entity
Predicate nearestCity P350 FINISHED
Object Aswan E11620 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: Aswan | Statement: [Gharb Sohail, nearestCity, Aswan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aswan
Context triple: [Gharb Sohail, nearestCity, Aswan]
  • A. Aswan chosen
    Aswan is a historic city in southern Egypt on the Nile River, known for its ancient temples, quarries, and the nearby Aswan High Dam.
  • B. Ismailia
    Ismailia is a city in northeastern Egypt on the west bank of the Suez Canal, known for its strategic location, colonial-era architecture, and role as an administrative center for the canal zone.
  • C. Assiut
    Assiut is a major city in Upper Egypt on the Nile River, serving as an important regional administrative, commercial, and transportation hub.
  • D. Shebin El Qanater
    Shebin El Qanater is a city in Egypt’s Qalyubia Governorate, located in the Nile Delta north of Cairo.
  • E. Tanta
    Tanta is a small Andean town in Peru known for its high-altitude landscapes and traditional rural life within the Nor Yauyos-Cochas scenic reserve.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a8be108190bad0021f95ce3a93 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69f74612bab88190bf1a895b87be12c1 completed May 3, 2026, 12:56 p.m.
Created at: April 9, 2026, 9:29 p.m.