Triple

T1764346
Position Surface form Disambiguated ID Type / Status
Subject Lichtenberg E38727 entity
Predicate contains P35 FINISHED
Object Wartenberg locality
Wartenberg locality is a residential district in the northeastern part of Berlin, Germany, known for its mix of housing estates and green spaces.
E196877 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: Wartenberg locality | Statement: [Lichtenberg, contains, Wartenberg locality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wartenberg locality
Context triple: [Lichtenberg, contains, Wartenberg locality]
  • A. Langendorf
    Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
  • B. Friedenau
    Friedenau is a residential district in southwestern Berlin known for its historic architecture, leafy streets, and literary heritage.
  • C. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • D. Wünsdorf
    Wünsdorf is a town in Brandenburg, Germany, historically notable as a major military garrison and command center, including serving as the site of the German Wehrmacht’s high command during World War II.
  • E. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • 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: Wartenberg locality
Triple: [Lichtenberg, contains, Wartenberg locality]
Generated description
Wartenberg locality is a residential district in the northeastern part of Berlin, Germany, known for its mix of housing estates and green spaces.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wartenberg locality
Target entity description: Wartenberg locality is a residential district in the northeastern part of Berlin, Germany, known for its mix of housing estates and green spaces.
  • A. Langendorf
    Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
  • B. Friedenau
    Friedenau is a residential district in southwestern Berlin known for its historic architecture, leafy streets, and literary heritage.
  • C. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • D. Wünsdorf
    Wünsdorf is a town in Brandenburg, Germany, historically notable as a major military garrison and command center, including serving as the site of the German Wehrmacht’s high command during World War II.
  • E. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa646665088190afa31bdf48f14316 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0f12fd8819099759ebcdfc19494 completed March 8, 2026, 4:16 p.m.
NEDg Description generation batch_69ada1e424f88190b070f28789121458 completed March 8, 2026, 4:20 p.m.
NED2 Entity disambiguation (via description) batch_69ada298cc1081909faef3bdecbcbfd0 completed March 8, 2026, 4:23 p.m.
Created at: March 4, 2026, 7:31 p.m.