Triple

T14573853
Position Surface form Disambiguated ID Type / Status
Subject Nivelles E341986 entity
Predicate hasHistoricalBuilding P1098 FINISHED
Object Tour Simone
Tour Simone is a historic tower in the Belgian city of Nivelles, notable as part of the town’s medieval architectural heritage.
E1105845 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: Tour Simone | Statement: [Nivelles, hasHistoricalBuilding, Tour Simone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tour Simone
Context triple: [Nivelles, hasHistoricalBuilding, Tour Simone]
  • A. Simone Tata
    Simone Tata is an Indian businesswoman best known for transforming Lakmé into a leading cosmetics brand and playing a key role in the Tata Group’s consumer business expansion.
  • B. Simoni
    Simoni is an Italian surname most notably associated with Gigi Simoni, a respected former football player and manager.
  • C. Simona
    Simona is a feminine given name commonly used in various European and Latin cultures, often associated with the female form of Simon.
  • D. Simone
    Simone is a feminine given name of Hebrew origin meaning "hearkening" or "one who listens," widely used across various cultures.
  • E. Simone
    Simone is a 2002 satirical science fiction film written and directed by Andrew Niccol about a digitally created actress who becomes a global sensation.
  • 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: Tour Simone
Triple: [Nivelles, hasHistoricalBuilding, Tour Simone]
Generated description
Tour Simone is a historic tower in the Belgian city of Nivelles, notable as part of the town’s medieval architectural heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tour Simone
Target entity description: Tour Simone is a historic tower in the Belgian city of Nivelles, notable as part of the town’s medieval architectural heritage.
  • A. Simone Tata
    Simone Tata is an Indian businesswoman best known for transforming Lakmé into a leading cosmetics brand and playing a key role in the Tata Group’s consumer business expansion.
  • B. Simoni
    Simoni is an Italian surname most notably associated with Gigi Simoni, a respected former football player and manager.
  • C. Simona
    Simona is a feminine given name commonly used in various European and Latin cultures, often associated with the female form of Simon.
  • D. Simone
    Simone is a feminine given name of Hebrew origin meaning "hearkening" or "one who listens," widely used across various cultures.
  • E. Simone
    Simone is a 2002 satirical science fiction film written and directed by Andrew Niccol about a digitally created actress who becomes a global sensation.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3f49d58819094fcd2a702e146cb completed April 14, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8acc788081909c41905785fa9a29 completed May 8, 2026, 7:03 a.m.
NEDg Description generation batch_69fd8be7d8988190807d4db477b91de0 completed May 8, 2026, 7:08 a.m.
NED2 Entity disambiguation (via description) batch_69fd8d506df4819092b52b0dde04bb4d completed May 8, 2026, 7:14 a.m.
Created at: April 10, 2026, 1:24 a.m.