Triple

T4342735
Position Surface form Disambiguated ID Type / Status
Subject A9 E97820 entity
Predicate passesNearCity P3945 FINISHED
Object Bayreuth E112998 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: Bayreuth | Statement: [A9, passesNearCity, Bayreuth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bayreuth
Context triple: [A9, passesNearCity, Bayreuth]
  • A. Bayreuth chosen
    Bayreuth is a city in northern Bavaria, Germany, best known for its association with composer Richard Wagner and its annual Bayreuth Festival of his operas.
  • B. Regensburg
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • C. Bamberg
    Bamberg is a historic city in northern Bavaria, Germany, renowned for its well-preserved medieval old town and status as a UNESCO World Heritage Site.
  • D. Nuremberg
    Nuremberg is a historic city in Bavaria, Germany, known for its medieval architecture and its role as the site of the post–World War II war crimes tribunals.
  • E. Schongau
    Schongau is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and location along the Romantic Road.
  • 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_69b34548402c819085ab68b27c235a87 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35188e71c8190a3e82fa8d959de94 completed March 12, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5dba2b49c81909b7bf87672d71611 completed March 14, 2026, 10:05 p.m.
Created at: March 12, 2026, 11:14 p.m.