Triple

T4249533
Position Surface form Disambiguated ID Type / Status
Subject Swabian Jura E95812 entity
Predicate majorTownOnEdge P54943 FINISHED
Object Tübingen E306426 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: Tübingen | Statement: [Swabian Jura, majorTownOnEdge, Tübingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tübingen
Context triple: [Swabian Jura, majorTownOnEdge, Tübingen]
  • A. Tübingen chosen
    Tübingen is a historic university town in southwestern Germany known for its well-preserved medieval old town and prestigious Eberhard Karls University.
  • B. Heidelberg
    Heidelberg is a suburb of Melbourne, Australia, known for its historic role in Australian Impressionism and its location along the Yarra River.
  • C. Heidelberg
    Heidelberg is a South African town known for its historical significance and role as a regional service and commercial center.
  • D. Heidelberg
    Heidelberg is a historic university city in southwestern Germany renowned for its picturesque old town, castle ruins, and one of Europe’s oldest universities.
  • E. Heilbronn
    Heilbronn is a city in the German state of Baden-Württemberg known for its industrial base, wine production, and role as a regional economic and educational hub.
  • 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_69b3453f759881909b91f01a1e82c036 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34f7d20b48190a404638c68c31026 completed March 12, 2026, 11:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c124d359ec819086420b7e00b8d630 completed March 23, 2026, 11:32 a.m.
Created at: March 12, 2026, 11:06 p.m.