Triple

T17766980
Position Surface form Disambiguated ID Type / Status
Subject Halberstadt E443531 entity
Predicate hasLandmark P105 FINISHED
Object Gleimhaus
Gleimhaus is a literary museum in Halberstadt, Germany, dedicated to the life, work, and extensive correspondence of 18th-century poet and collector Johann Wilhelm Ludwig Gleim.
 E1286765 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: Gleimhaus | Statement: [Halberstadt, hasLandmark, Gleimhaus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gleimhaus
Context triple: [Halberstadt, hasLandmark, Gleimhaus]
  • A. Nattenhausen
    Nattenhausen is a small village in the Bavarian district of Günzburg in southern Germany.
  • B. Egenhausen
    Egenhausen is a small municipality in southwestern Germany, known for its rural setting and surrounding natural landscapes.
  • C. Harthausen
    Harthausen is a village-level subdivision of the municipality of Igersheim in the Main-Tauber district of Baden-Württemberg, Germany.
  • D. Eilshausen
    Eilshausen is a village and district within the municipality of Hiddenhausen in North Rhine-Westphalia, Germany.
  • E. Saalhof
    Saalhof is a historic medieval building complex in Frankfurt am Main that forms part of the city’s museum landscape and reflects its architectural and urban history.
  • 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: Gleimhaus
Triple: [Halberstadt, hasLandmark, Gleimhaus]
Generated description
Gleimhaus is a literary museum in Halberstadt, Germany, dedicated to the life, work, and extensive correspondence of 18th-century poet and collector Johann Wilhelm Ludwig Gleim.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gleimhaus
Target entity description: Gleimhaus is a literary museum in Halberstadt, Germany, dedicated to the life, work, and extensive correspondence of 18th-century poet and collector Johann Wilhelm Ludwig Gleim.
  • A. Nattenhausen
    Nattenhausen is a small village in the Bavarian district of Günzburg in southern Germany.
  • B. Egenhausen
    Egenhausen is a small municipality in southwestern Germany, known for its rural setting and surrounding natural landscapes.
  • C. Harthausen
    Harthausen is a village-level subdivision of the municipality of Igersheim in the Main-Tauber district of Baden-Württemberg, Germany.
  • D. Eilshausen
    Eilshausen is a village and district within the municipality of Hiddenhausen in North Rhine-Westphalia, Germany.
  • E. Saalhof
    Saalhof is a historic medieval building complex in Frankfurt am Main that forms part of the city’s museum landscape and reflects its architectural and urban history.
  • 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_69d8b9edf16c8190a59ebd245d378f4f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e485fccb9881908923564bf319f3c1 completed April 19, 2026, 7:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02efc14808819099ecbb8a752aff24 completed May 12, 2026, 9:15 a.m.
NEDg Description generation batch_6a02f096fc648190a1ff19f2704a4cef completed May 12, 2026, 9:19 a.m.
NED2 Entity disambiguation (via description) batch_6a02f1d0a4708190bbf51356da7e965e completed May 12, 2026, 9:24 a.m.
Created at: April 10, 2026, 10:11 a.m.