Triple

T17143624
Position Surface form Disambiguated ID Type / Status
Subject TGV Est E416032 entity
Predicate connectsCity P4245 FINISHED
Object Frankfurt am Main 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: Frankfurt am Main | Statement: [TGV Est, connectsCity, Frankfurt am Main]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frankfurt am Main
Context triple: [TGV Est, connectsCity, Frankfurt am Main]
  • A. Frankfurt am Main chosen
    Frankfurt am Main is a major German financial and transportation hub on the River Main, known for hosting the European Central Bank and one of Europe’s busiest airports.
  • B. Frankfurt Rhine-Main
    Frankfurt Rhine-Main is a major metropolitan region in western Germany centered around Frankfurt am Main, known as a key European hub for finance, transportation, and commerce.
  • C. Wiesbaden
    Wiesbaden is a historic spa city in western Germany known for its thermal springs, elegant architecture, and role as a regional administrative and cultural center.
  • D. Mannheim
    Mannheim is a major city in southwestern Germany, known as an important industrial, commercial, and cultural center at the confluence of the Rhine and Neckar rivers.
  • E. Cologne
    Cologne is a historic German city on the Rhine River, renowned for its Gothic cathedral, vibrant cultural scene, and status as a major economic and media hub.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f2d73c3c81908b875023bb925edb completed April 18, 2026, 9:08 p.m.
Created at: April 10, 2026, 5:36 a.m.