Triple

T801440
Position Surface form Disambiguated ID Type / Status
Subject Upper Egypt E17135 entity
Predicate extendsTo P1673 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: [Upper Egypt, extendsTo, Aswan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aswan
Context triple: [Upper Egypt, extendsTo, 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. Tanta
    Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
  • E. Mansoura
    Mansoura is a major city in Egypt’s Nile Delta, serving as an important regional center for agriculture, commerce, and transportation.
  • 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_69a49378b9c48190adbf5f62e5b7aca1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a7cc75e88190bd35aabe51051b51 completed March 1, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c7103a00819087ad711a2ab99770 completed March 4, 2026, 5:45 a.m.
Created at: March 1, 2026, 7:38 p.m.