Triple

T213135
Position Surface form Disambiguated ID Type / Status
Subject Egyptian National Railways network E4759 entity
Predicate connects P390 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: [Egyptian National Railways network, connects, Aswan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aswan
Context triple: [Egyptian National Railways network, connects, 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. Assiut
    Assiut is a major city in Upper Egypt on the Nile River, serving as an important regional administrative, commercial, and transportation hub.
  • C. Sohag
    Sohag is a city in Upper Egypt that serves as the capital of the Sohag Governorate and an important regional center along the Nile.
  • D. Cairo
    Cairo is the capital and largest city of Egypt, a historic metropolis on the Nile renowned for its rich Islamic heritage and proximity to the ancient pyramids.
  • E. Minya
    Minya is a major city in Upper Egypt on the Nile River, serving as an important regional administrative and commercial center.
  • 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_69a2575cb1dc8190a01ad332426dc339 completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c313d108190a65d3e939f961bef completed Feb. 28, 2026, 3:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3d4dcaec0819099f5a3721d035cdd completed March 1, 2026, 5:55 a.m.
Created at: Feb. 28, 2026, 2:52 a.m.