Triple

T5439044
Position Surface form Disambiguated ID Type / Status
Subject Altes AKH campus E122084 entity
Predicate locatedIn P40 FINISHED
Object Alsergrund E348815 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: Alsergrund | Statement: [Altes AKH campus, locatedIn, Alsergrund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alsergrund
Context triple: [Altes AKH campus, locatedIn, Alsergrund]
  • A. Alsergrund chosen
    Alsergrund is the 9th district of Vienna, Austria, known for its historic architecture, cultural institutions, and proximity to the city center.
  • B. Riedergarten
    Riedergarten is a historic public garden and popular green oasis located in the Bavarian city of Rosenheim, Germany.
  • C. Adlershof
    Adlershof is a district in Berlin, Germany, known as a major science, technology, and media hub featuring research institutes, universities, and high-tech companies.
  • D. Gartenstadt
    Gartenstadt is a residential district of the Upper Franconian town of Lichtenfels in Bavaria, Germany.
  • E. Magniviertel
    Magniviertel is a historic quarter in Braunschweig, Germany, known for its medieval street layout, half-timbered houses, and lively cultural and nightlife scene.
  • 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_69bd46400768819092925d461c0b8432 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd91be61dc819087f4a77bdc5ff382 completed March 20, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3ad3a3d88190bacde12f515d9971 completed March 22, 2026, 12:41 a.m.
Created at: March 20, 2026, 2:07 p.m.