Triple

T23015105
Position Surface form Disambiguated ID Type / Status
Subject Nikolassee station E573010 entity
Predicate fareZone P844 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: [Nikolassee station, fareZone, VBB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VBB
Context triple: [Nikolassee station, fareZone, 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. VABV
    VABV is the ICAO airport code assigned to Bhavnagar Airport in Gujarat, India.
  • D. 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.
  • E. 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.
  • 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_69e245b764cc8190a51be76f1d9611e1 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f183e3c0e08190a7ac747b056ec3ca completed April 29, 2026, 4:06 a.m.
Created at: April 17, 2026, 3:51 p.m.