Triple

T16158269
Position Surface form Disambiguated ID Type / Status
Subject Graben E392108 entity
Predicate connectsTo P845 FINISHED
Object Tuchlauben E1117267 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: Tuchlauben | Statement: [Graben, connectsTo, Tuchlauben]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tuchlauben
Context triple: [Graben, connectsTo, Tuchlauben]
  • A. Tuchlauben chosen
    Tuchlauben is a historic street in Vienna’s city center, known for its upscale shops and proximity to major landmarks in the old town.
  • B. Nebelschütz
    Nebelschütz is a small municipality in eastern Saxony, Germany, known for its Sorbian cultural heritage and rural setting.
  • C. Schlawe
    Schlawe is a historic town in Pomerania, formerly in Prussia and now known as Sławno in northwestern Poland.
  • D. Ehlhalten
    Ehlhalten is a village and district of the town of Eppstein in the Rheingau-Taunus region of Hesse, Germany.
  • E. Von der Tann
    Von der Tann was the Imperial German Navy’s first battlecruiser, notable for combining heavy armament with high speed and influencing subsequent German capital ship designs.
  • 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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21e5c9cd0819090e34ee163ffb118 completed April 17, 2026, 11:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7b05a588190a44d1c922195a87b completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:01 a.m.