Triple

T4286774
Position Surface form Disambiguated ID Type / Status
Subject Odenwald E97287 entity
Predicate containsTown P847 FINISHED
Object Michelstadt E188118 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: Michelstadt | Statement: [Odenwald, containsTown, Michelstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michelstadt
Context triple: [Odenwald, containsTown, Michelstadt]
  • A. Korbach
    Korbach is a historic town in the German state of Hesse, known as the district seat of Waldeck-Frankenberg and for its well-preserved medieval old town.
  • B. Borgholzhausen
    Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
  • C. Weiterstadt chosen
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • D. Suhl
    Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
  • E. Neustadt an der Aisch
    Neustadt an der Aisch is a small town in the Bavarian region of Germany, known for its historic center and location along the Aisch River between Würzburg and Nuremberg.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3505d23d88190a638f2cc2acee9ee completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd36a7c9c81908f325bc8a53db0c8 completed March 20, 2026, 11:08 p.m.
Created at: March 12, 2026, 11:08 p.m.