Triple

T9718598
Position Surface form Disambiguated ID Type / Status
Subject Hejaz Railway E235404 entity
Predicate connects P390 FINISHED
Object Medina E28127 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: Medina | Statement: [Hejaz Railway, connects, Medina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medina
Context triple: [Hejaz Railway, connects, Medina]
  • A. Medina chosen
    Medina is a holy city in western Saudi Arabia that is revered in Islam as the site of the Prophet Muhammad’s mosque and tomb and the second-holiest city after Mecca.
  • B. Medina
    Medina is a small suburban city in Minnesota known for its rural character, parks, and proximity to the Minneapolis–Saint Paul metropolitan area.
  • C. Medina
    Medina is a coastal municipality in the Philippines known for its scenic shoreline along Macajalar Bay and its largely rural, agriculture-based communities.
  • D. Medina
    Medina is a common Spanish-origin surname found across the Spanish-speaking world and among their diasporas.
  • E. Medina
    Medina was a Spanish women's magazine associated with the Franco-era Sección Femenina that promoted traditional gender roles and nationalist ideology.
  • 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_69ca84d0123c819096f9dc3b6abb0881 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e3ea61081908a5671fc5be9a738 completed April 1, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc408b988190980db82fbd93e988 completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:20 p.m.