Triple

T17645322
Position Surface form Disambiguated ID Type / Status
Subject Tiel railway station E429340 entity
Predicate serves P98 FINISHED
Object Tiel NE NERFINISHED

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: Tiel | Statement: [Tiel railway station, serves, Tiel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tiel
Context triple: [Tiel railway station, serves, Tiel]
  • A. Tiel chosen
    Tiel is a historic Dutch city situated along the River Waal, known for its fruit cultivation and role as a regional trade center in the province of Gelderland.
  • B. Tjuchem
    Tjuchem is a small village in the province of Groningen in the Netherlands, known for its rural character and agricultural surroundings.
  • C. Tiba
    Tiba is a modern planned city in Egypt’s Luxor Governorate, developed to accommodate population growth and support regional economic and urban expansion.
  • D. Tachov
    Tachov is a town in western Czechia that serves as an administrative center and local hub within the Plzeň Region.
  • E. Taucha
    Taucha is a small town in the German state of Saxony, located just northeast of Leipzig and closely integrated into its urban and economic area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e2c2608190b762e76d9b2262f1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46e382ba88190af19d0e3b8c8cadd completed April 19, 2026, 5:55 a.m.
Created at: April 10, 2026, 6:04 a.m.