Triple

T4296401
Position Surface form Disambiguated ID Type / Status
Subject Valentinswerder E99723 entity
Predicate locatedNorthOf P305 FINISHED
Object Tegelort E2522 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: Tegelort | Statement: [Valentinswerder, locatedNorthOf, Tegelort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tegelort
Context triple: [Valentinswerder, locatedNorthOf, Tegelort]
  • A. Tempelhof
    Tempelhof is a historic district in Berlin, Germany, best known for the former Tempelhof Airport and its vast airfield now used as a public park.
  • B. Tegel chosen
    Tegel is a locality in the Reinickendorf borough of Berlin, Germany, historically known for its manor associated with the Humboldt family and later for the former Berlin Tegel Airport.
  • C. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • D. Gatow
    Gatow is a village-like locality in southwestern Berlin known for its former airfield and proximity to the Havel River and surrounding green spaces.
  • E. Lilienthal
    Lilienthal is a German-origin surname borne by various notable individuals, including figures in aviation, science, and public service.
  • 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_69b3455175088190aa79c6e03b86647e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3509aebd48190af38f2e37f07869a completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c7439b3481908d2554f7b86002aa completed March 14, 2026, 8:38 p.m.
Created at: March 12, 2026, 11:08 p.m.