Triple

T5672851
Position Surface form Disambiguated ID Type / Status
Subject White Crown E125016 entity
Predicate associatedCity P3207 FINISHED
Object Elkab E425336 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: Elkab | Statement: [White Crown, associatedCity, Elkab]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elkab
Context triple: [White Crown, associatedCity, Elkab]
  • A. Elkab chosen
    Elkab is an ancient Egyptian city and archaeological site in Upper Egypt, notable as a major cult center of the vulture goddess Nekhbet.
  • B. Aswan
    Aswan is a historic city in southern Egypt on the Nile River, known for its ancient temples, quarries, and the nearby Aswan High Dam.
  • C. Ain Sokhna
    Ain Sokhna is a popular Egyptian Red Sea resort town known for its beaches, proximity to Cairo, and role as a growing industrial and port area.
  • D. Qurna
    Qurna is a town in southern Iraq near the confluence of the Tigris and Euphrates rivers, historically significant as a strategic site during World War I.
  • E. Gash‑Barka
    Gash‑Barka is a largely agricultural region in southwestern Eritrea known for its fertile land and role as one of the country’s main food-producing areas.
  • 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_69c008295c808190acfe78915e7d656a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0236e8dc48190b4eb7709a258909f completed March 22, 2026, 5:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04db5c9a08190b1d6b7db87d0d9ac completed March 22, 2026, 8:14 p.m.
Created at: March 22, 2026, 3:43 p.m.