Triple

T21829082
Position Surface form Disambiguated ID Type / Status
Subject Wittenbergplatz station E538937 entity
Predicate fareSystem P395 FINISHED
Object VBB NE NERFINISHED

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: VBB | Statement: [Wittenbergplatz station, fareSystem, VBB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VBB
Context triple: [Wittenbergplatz station, fareSystem, VBB]
  • A. VBB chosen
    VBB is the public transport authority and fare network that coordinates and integrates regional and urban transit services across Berlin and the surrounding Brandenburg region.
  • B. VABB
    VABB is the ICAO airport code for Chhatrapati Shivaji Maharaj International Airport, the primary international airport serving Mumbai, India.
  • C. VBB: Berlin AB
    VBB: Berlin AB is the central fare zone of Berlin’s public transport network, covering the inner city area served by buses, trams, U-Bahn, and S-Bahn.
  • D. VAB
    VAB is the commonly used abbreviation for NASA’s Vehicle Assembly Building, the massive structure at Kennedy Space Center where rockets are assembled before launch.
  • E. BVC
    BVC is the Indian Railways station code for Bhavnagar Terminus railway station in Gujarat, India.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c475cda88190987d08f23caebdc1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f091344c848190b1675432a8c255f2 completed April 28, 2026, 10:51 a.m.
Created at: April 16, 2026, 6:54 p.m.