Triple

T11854167
Position Surface form Disambiguated ID Type / Status
Subject Erfurt E281989 entity
Predicate hasPart P35 FINISHED
Object Erfurt old town E281989 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: Erfurt old town | Statement: [Erfurt, hasPart, Erfurt old town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erfurt old town
Context triple: [Erfurt, hasPart, Erfurt old town]
  • A. Erfurt chosen
    Erfurt is a historic German city in the state of Thuringia, known for its well-preserved medieval old town and as an important cultural and educational center.
  • B. Eisenach
    Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
  • C. Altstadt Gera
    Altstadt Gera is the historic old town district of Gera, Germany, characterized by preserved architecture, traditional squares, and cultural landmarks reflecting the city’s past.
  • D. Rothenburg ob der Tauber
    Rothenburg ob der Tauber is a well-preserved medieval town in Bavaria, Germany, famed for its intact city walls, half-timbered houses, and picturesque old town.
  • E. Rothenburg
    Rothenburg is a locality within the town of Wettin-Löbejün in the German state of Saxony-Anhalt.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a697f4108190af984932d2118472 completed April 10, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69f167c9d4e88190bfaadada0450e639 completed April 29, 2026, 2:07 a.m.
Created at: April 8, 2026, 9:43 p.m.