Triple

T17009682
Position Surface form Disambiguated ID Type / Status
Subject Estates Theatre E412664 entity
Predicate architect P184 FINISHED
Object Anton Haffenecker
Anton Haffenecker was an 18th-century architect best known for designing Prague’s historic Estates Theatre.
E1244613 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: Anton Haffenecker | Statement: [Estates Theatre, architect, Anton Haffenecker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anton Haffenecker
Context triple: [Estates Theatre, architect, Anton Haffenecker]
  • A. Heinz Suter
    Heinz Suter is a Swiss former footballer known for his career in the Swiss domestic leagues during the 1970s and 1980s.
  • B. Bruno Bischofberger
    Bruno Bischofberger is a prominent Swiss art dealer and gallerist known for championing contemporary and Pop Art, including the work of artists like Andy Warhol and Jean-Michel Basquiat.
  • C. Christian Vogt
    Christian Vogt is a German local politician who serves as the mayor of the town of Hofheim am Taunus in Hesse.
  • D. Tom Nissalke
    Tom Nissalke was an American professional basketball coach best known for his work in the ABA and NBA during the 1970s and 1980s.
  • E. Pascal Jost
    Pascal Jost is a French local politician serving as the mayor of the commune of Veckring in northeastern France.
  • 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: Anton Haffenecker
Triple: [Estates Theatre, architect, Anton Haffenecker]
Generated description
Anton Haffenecker was an 18th-century architect best known for designing Prague’s historic Estates Theatre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Anton Haffenecker
Target entity description: Anton Haffenecker was an 18th-century architect best known for designing Prague’s historic Estates Theatre.
  • A. Heinz Suter
    Heinz Suter is a Swiss former footballer known for his career in the Swiss domestic leagues during the 1970s and 1980s.
  • B. Bruno Bischofberger
    Bruno Bischofberger is a prominent Swiss art dealer and gallerist known for championing contemporary and Pop Art, including the work of artists like Andy Warhol and Jean-Michel Basquiat.
  • C. Christian Vogt
    Christian Vogt is a German local politician who serves as the mayor of the town of Hofheim am Taunus in Hesse.
  • D. Tom Nissalke
    Tom Nissalke was an American professional basketball coach best known for his work in the ABA and NBA during the 1970s and 1980s.
  • E. Pascal Jost
    Pascal Jost is a French local politician serving as the mayor of the commune of Veckring in northeastern France.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47a8444819081f1262eb7dbda40 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc241ec88190a3e868ab88b26f09 completed May 10, 2026, 7:27 p.m.
NEDg Description generation batch_6a0114d7d03c8190943777f4eac956fd completed May 10, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a01159a08b081908fc82adc7cca532a completed May 10, 2026, 11:32 p.m.
Created at: April 10, 2026, 5:33 a.m.