Triple

T15157315
Position Surface form Disambiguated ID Type / Status
Subject Berlin AB E362110 entity
Predicate adjacentTo P224 FINISHED
Object Berlin C E578128 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: Berlin C | Statement: [Berlin AB, adjacentTo, Berlin C]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin C
Context triple: [Berlin AB, adjacentTo, Berlin C]
  • A. Berlin C chosen
    Berlin C is the outer suburban ring of the Berlin public transport network, covering surrounding areas outside the city’s core zones A and B.
  • B. Berlin B
    Berlin B is one of the public transport fare zones in Berlin, covering the outer areas of the city beyond the central A zone.
  • C. Berlin
    Berlin is the capital and largest city of Germany, historically significant as a focal point of Cold War tensions and a major cultural, political, and economic center in Europe.
  • D. Berlin
    Berlin is a charismatic, calculating, and morally ambiguous mastermind and heist leader in the Spanish television series "Money Heist" (La Casa de Papel).
  • E. Berlin
    Berlin is a borough in Camden County, New Jersey, known as a suburban community within the Philadelphia metropolitan area.
  • 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_69d85a0759908190b8a051d2e2a1cbe6 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0060c62b08190bcdbd912d011d1ba completed April 15, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69febff87b6c819097f5cc99b2d75fb6 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3:08 a.m.