Triple

T2781149
Position Surface form Disambiguated ID Type / Status
Subject Römerberg E61696 entity
Predicate district P2709 FINISHED
Object Altstadt E193725 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: Altstadt | Statement: [Römerberg, district, Altstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Altstadt
Context triple: [Römerberg, district, Altstadt]
  • A. Altstadt
    Altstadt is the historic old town of Salzburg, Austria, renowned for its well-preserved baroque architecture and status as a UNESCO World Heritage Site.
  • B. Altstadt chosen
    Altstadt is the historic old town of Düsseldorf, Germany, known for its dense concentration of bars, traditional breweries, and cultural landmarks along the Rhine River.
  • C. Altstadt
    Altstadt is the historic old town district of Dresden, Germany, known for its baroque architecture and major cultural landmarks.
  • D. Old Town (Altstadt)
    Old Town (Altstadt) is Cologne’s historic city center, known for its narrow cobbled streets, traditional houses, and numerous breweries and pubs near the Rhine.
  • E. Stadtmitte
    Stadtmitte is a central Berlin U-Bahn station serving as an important interchange and access point to the city’s historic Mitte district.
  • 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_69ab4b7e43c48190997b8fc8fb1663ab completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd997ebc8190bff88fe549827615 completed March 7, 2026, 8:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc05f4e7881908bf5b6f7df331041 completed March 10, 2026, 6:55 a.m.
Created at: March 6, 2026, 9:57 p.m.