Triple

T3842356
Position Surface form Disambiguated ID Type / Status
Subject Pankow E93479 entity
Predicate contains P35 FINISHED
Object Pankow locality E93479 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: Pankow locality | Statement: [Pankow, contains, Pankow locality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pankow locality
Context triple: [Pankow, contains, Pankow locality]
  • A. Pankow chosen
    Pankow is a northeastern borough of Berlin known for its mix of historic neighborhoods, green spaces, and the popular district of Prenzlauer Berg.
  • B. Friedrichsfelde locality
    Friedrichsfelde is a residential and historically significant locality in the Berlin borough of Lichtenberg, known among other things for the Tierpark Berlin zoo and its post-war urban architecture.
  • C. Tegel district
    Tegel district is a locality in Berlin’s Reinickendorf borough known for its mix of residential areas, industrial sites, and proximity to Lake Tegel and the former Berlin Tegel Airport.
  • D. Reinickendorf
    Reinickendorf is a borough in the northwest of Berlin, Germany, known for its mix of residential neighborhoods, industrial areas, and green spaces including parts of Lake Tegel.
  • E. Treptow-Köpenick
    Treptow-Köpenick is Berlin’s largest and greenest borough, known for its extensive forests, lakes, and historic town centers such as Köpenick.
  • 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_69aed96ce578819084ab16e3439976c9 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeebb397ac81908f74a42a0eeb8682 completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd7f58290881908c7622616a829c75 completed March 20, 2026, 5:09 p.m.
Created at: March 9, 2026, 3:18 p.m.