Triple

T9364311
Position Surface form Disambiguated ID Type / Status
Subject district of Dachau E225361 entity
Predicate contains P35 FINISHED
Object Haimhausen
Haimhausen is a small municipality in Upper Bavaria, Germany, known for its historic castle and rural setting north of Munich.
E849363 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: Haimhausen | Statement: [district of Dachau, contains, Haimhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haimhausen
Context triple: [district of Dachau, contains, Haimhausen]
  • A. Balzhausen
    Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
  • B. Marlenheim
    Marlenheim is a commune in northeastern France’s Alsace region, known as a historic wine-producing village and gateway to the area’s renowned vineyards and scenic countryside.
  • C. Merzhausen
    Merzhausen is a village-level district that forms one of the subdivisions of the town of Usingen in the Hochtaunus region of Hesse, Germany.
  • D. Schaafheim
    Schaafheim is a municipality in the state of Hesse in central Germany.
  • E. Wilhelmsruh
    Wilhelmsruh is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and historical ties to Berlin’s former border zone.
  • 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: Haimhausen
Triple: [district of Dachau, contains, Haimhausen]
Generated description
Haimhausen is a small municipality in Upper Bavaria, Germany, known for its historic castle and rural setting north of Munich.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Haimhausen
Target entity description: Haimhausen is a small municipality in Upper Bavaria, Germany, known for its historic castle and rural setting north of Munich.
  • A. Balzhausen
    Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
  • B. Marlenheim
    Marlenheim is a commune in northeastern France’s Alsace region, known as a historic wine-producing village and gateway to the area’s renowned vineyards and scenic countryside.
  • C. Merzhausen
    Merzhausen is a village-level district that forms one of the subdivisions of the town of Usingen in the Hochtaunus region of Hesse, Germany.
  • D. Schaafheim
    Schaafheim is a municipality in the state of Hesse in central Germany.
  • E. Wilhelmsruh
    Wilhelmsruh is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and historical ties to Berlin’s former border zone.
  • 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_69ca842bdd648190904131d58620d448 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd503fd7f081909655e2a880c84834 completed April 1, 2026, 5:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69d6525a4af08190bcd8455e95a2f3ae completed April 8, 2026, 1:04 p.m.
NEDg Description generation batch_69d65348c988819083f4c8008a1f8cf7 completed April 8, 2026, 1:08 p.m.
NED2 Entity disambiguation (via description) batch_69d654b44070819098e1148e9dbd8a11 completed April 8, 2026, 1:14 p.m.
Created at: March 30, 2026, 7:42 p.m.