Triple

T14755915
Position Surface form Disambiguated ID Type / Status
Subject Hoher Markt E346727 entity
Predicate hasNearbyStreet P8235 FINISHED
Object Rotenturmstraße E1089245 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: Rotenturmstraße | Statement: [Hoher Markt, hasNearbyStreet, Rotenturmstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rotenturmstraße
Context triple: [Hoher Markt, hasNearbyStreet, Rotenturmstraße]
  • A. Rotenturmstraße chosen
    Rotenturmstraße is a prominent shopping and pedestrian street in central Vienna, Austria, linking Stephansplatz with the Danube Canal area and known for its historic buildings and lively commercial atmosphere.
  • B. Junghofstraße
    Junghofstraße is a street in central Frankfurt am Main, Germany, located near the Taunusanlage area and its major transit connections.
  • C. Beusselstraße
    Beusselstraße is a railway station in Berlin that serves the city's circular Ringbahn line and connects the surrounding Moabit area to the wider S-Bahn network.
  • D. Eichhornstraße
    Eichhornstraße is a street in central Berlin, Germany, located near Leipziger Platz in the city’s historic and commercial district.
  • E. Bräunerstraße
    Bräunerstraße is a street in Vienna’s historic city center, known for its upscale shops, historic buildings, and proximity to major landmarks such as the Graben.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7ef0fd48190bd4a8af128ef274c completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a5f38488190b441dd0b385024b1 completed May 9, 2026, 11:28 a.m.
Created at: April 10, 2026, 1:30 a.m.