Triple

T7149034
Position Surface form Disambiguated ID Type / Status
Subject Debis-Haus E166642 entity
Predicate namedAfter P63 FINISHED
Object Debis E645673 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: Debis | Statement: [Debis-Haus, namedAfter, Debis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Debis
Context triple: [Debis-Haus, namedAfter, Debis]
  • A. Debis chosen
    Debis was the real estate and property development arm of the former Daimler-Benz group, involved in major projects such as the redevelopment of Potsdamer Platz in Berlin.
  • B. Dausa
    Dausa is a town and district headquarters in the Indian state of Rajasthan, known for its historical forts, stepwells, and proximity to Jaipur.
  • C. Debica
    Debica is a tire brand owned by the Goodyear Tire & Rubber Company, known for producing affordable passenger and commercial vehicle tires, particularly in European markets.
  • D. Dishna
    Dishna is a town in Egypt’s Qena Governorate, located in Upper Egypt along the Nile and known for its agricultural surroundings.
  • E. Badesi
    Badesi is a coastal town and comune in the Gallura region of northern Sardinia, Italy, known for its long sandy beaches and tourism.
  • 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_69c68886779c8190a8e3fbabffe68253 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e7f130e08190bc5ca99f90f9de92 completed March 27, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b8ee0244819084d5dfb3ee64149b completed March 28, 2026, 11:18 a.m.
Created at: March 27, 2026, 2:46 p.m.