Triple

T12103410
Position Surface form Disambiguated ID Type / Status
Subject Aswan Low Dam E288243 entity
Predicate locatedNear P294 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: [Aswan Low Dam, locatedNear, Aswan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aswan
Context triple: [Aswan Low Dam, locatedNear, 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_69d6ab4a5c448190a110d1273314b21a completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915568b9881909fc9edacefb86409 completed April 10, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a7140c4819086a2dcb2cf334963 completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:48 p.m.