Triple

T3435991
Position Surface form Disambiguated ID Type / Status
Subject Alt-Tempelhof E72452 entity
Predicate locatedIn P40 FINISHED
Object 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.
E381479 NE FINISHED

How this triple was built (4 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: Tempelhof | Statement: [Alt-Tempelhof, locatedIn, Tempelhof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tempelhof
Context triple: [Alt-Tempelhof, locatedIn, Tempelhof]
  • A. Tempelhof Airport
    Tempelhof Airport is a historic Berlin airfield best known as a central hub of the Berlin Airlift during the Cold War.
  • B. Tegel
    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. Alt-Tempelhof
    Alt-Tempelhof is an underground station on Berlin’s U-Bahn network serving the Tempelhof district in the southern part of the city.
  • D. Spandau
    Spandau is a western borough of Berlin, Germany, known for its historic old town, fortress, and role as an important residential and industrial district.
  • E. Schönefeld
    Schönefeld is a municipality just southeast of Berlin in the German state of Brandenburg, known for hosting the Berlin Brandenburg Airport.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tempelhof
Triple: [Alt-Tempelhof, locatedIn, Tempelhof]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tempelhof
Target entity description: 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.
  • A. Tempelhof Airport
    Tempelhof Airport is a historic Berlin airfield best known as a central hub of the Berlin Airlift during the Cold War.
  • B. Tegel
    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. Alt-Tempelhof
    Alt-Tempelhof is an underground station on Berlin’s U-Bahn network serving the Tempelhof district in the southern part of the city.
  • D. Spandau
    Spandau is a western borough of Berlin, Germany, known for its historic old town, fortress, and role as an important residential and industrial district.
  • E. Schönefeld
    Schönefeld is a municipality just southeast of Berlin in the German state of Brandenburg, known for hosting the Berlin Brandenburg Airport.
  • F. None of above. chosen

Provenance (5 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_69ad85af50288190a854b76653deee6f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb9f2e4b4819085336fb539daf3c7 completed March 8, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4cdc9089481909e9ef5f5e7edeaa6 completed March 14, 2026, 2:54 a.m.
NEDg Description generation batch_69b4cf5535748190b5dc3f23d1692e51 completed March 14, 2026, 3 a.m.
NED2 Entity disambiguation (via description) batch_69b4cfc29a18819087935c16f6ecd9e4 completed March 14, 2026, 3:02 a.m.
Created at: March 8, 2026, 3:16 p.m.