Triple

T6110895
Position Surface form Disambiguated ID Type / Status
Subject Alexanderplatz E136235 entity
Predicate formerName P65 FINISHED
Object Ochsenplatz E571129 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: Ochsenplatz | Statement: [Alexanderplatz, formerName, Ochsenplatz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ochsenplatz
Context triple: [Alexanderplatz, formerName, Ochsenplatz]
  • A. Ochsenmarkt chosen
    Ochsenmarkt was the historical marketplace in Berlin that later became known as Alexanderplatz, once a central hub for trade and urban life.
  • B. Burgplatz
    Burgplatz is a historic central square in Braunschweig, Germany, known for its medieval architecture and prominent landmarks such as Dankwarderode Castle and the Brunswick Lion.
  • C. Sechseläutenplatz
    Sechseläutenplatz is a major public square in central Zurich, Switzerland, known for hosting cultural events and festivals and for being one of the city’s largest urban plazas.
  • D. Barfüsserplatz
    Barfüsserplatz is a central public square in Basel, Switzerland, known as a major tram hub and venue for markets and city events.
  • E. Leopoldplatz
    Leopoldplatz is a major public square and important transport hub in Berlin’s Wedding district, served by multiple U-Bahn lines and numerous bus routes.
  • 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_69c0089ea6f88190b349be53e04b4f5f completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bbbbea88190b889a7c30af1d71a completed March 22, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141619c148190b0fb94e2b1458510 completed March 23, 2026, 1:34 p.m.
Created at: March 22, 2026, 4:13 p.m.