Triple

T4890316
Position Surface form Disambiguated ID Type / Status
Subject Eichig E109541 entity
Predicate hasPostalAddressIn P4379 FINISHED
Object Lichtenfels E11679 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: Lichtenfels | Statement: [Eichig, hasPostalAddressIn, Lichtenfels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lichtenfels
Context triple: [Eichig, hasPostalAddressIn, Lichtenfels]
  • A. Lichtenfels chosen
    Lichtenfels is a town in the Upper Franconia region of Bavaria, Germany, known for its basket-making tradition and historic architecture.
  • B. Markranstädt
    Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
  • C. Lampoldshausen
    Lampoldshausen is a German village best known as a major site for rocket propulsion research and testing facilities of the German Aerospace Center.
  • D. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • E. Mühlhausen
    Mühlhausen is a historic town in central Germany, known for its well-preserved medieval architecture and cultural heritage.
  • 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_69bd440f71348190b99938e59fb7f9a1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e07ca10819083f80f12374544b1 completed March 20, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea4623ae881908f5dac4eaa56f91d completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:28 p.m.