Triple

T1903722
Position Surface form Disambiguated ID Type / Status
Subject MAN E37749 entity
Predicate notableWork P4 FINISHED
Object MAN Lion’s City
MAN Lion’s City is a popular series of low-floor city buses produced by the German manufacturer MAN for urban public transport.
 E212635 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: MAN Lion’s City | Statement: [MAN, notableWork, MAN Lion’s City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAN Lion’s City
Context triple: [MAN, notableWork, MAN Lion’s City]
  • A. Mike City
    Mike City is an American R&B songwriter and producer best known for crafting hits for artists like Sunshine Anderson, Brandy, and Carl Thomas.
  • B. Blue City
    Blue City is a popular nickname for Jodhpur, a historic city in Rajasthan, India, famed for its blue-painted houses and hilltop Mehrangarh Fort.
  • C. Silk City
    Silk City is a historic nickname for Paterson, New Jersey, reflecting its past prominence as a major center of silk production in the United States.
  • D. Silk City
    Silk City is a popular nickname for Rajshahi, a major city in western Bangladesh historically renowned for its silk industry and fine silk products.
  • E. Red City
    Red City is a popular nickname for Marrakesh, the historic Moroccan metropolis famed for its reddish sandstone buildings and city walls.
  • 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: MAN Lion’s City
Triple: [MAN, notableWork, MAN Lion’s City]
Generated description
MAN Lion’s City is a popular series of low-floor city buses produced by the German manufacturer MAN for urban public transport.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MAN Lion’s City
Target entity description: MAN Lion’s City is a popular series of low-floor city buses produced by the German manufacturer MAN for urban public transport.
  • A. Mike City
    Mike City is an American R&B songwriter and producer best known for crafting hits for artists like Sunshine Anderson, Brandy, and Carl Thomas.
  • B. Blue City
    Blue City is a popular nickname for Jodhpur, a historic city in Rajasthan, India, famed for its blue-painted houses and hilltop Mehrangarh Fort.
  • C. Silk City
    Silk City is a historic nickname for Paterson, New Jersey, reflecting its past prominence as a major center of silk production in the United States.
  • D. Silk City
    Silk City is a popular nickname for Rajshahi, a major city in western Bangladesh historically renowned for its silk industry and fine silk products.
  • E. Red City
    Red City is a popular nickname for Marrakesh, the historic Moroccan metropolis famed for its reddish sandstone buildings and city walls.
  • 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_69a8861be7148190a680937ec451a304 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1909aec8190b3259c8f969ce81e completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeaf768888190885ffa1632537445 completed March 8, 2026, 9:32 p.m.
NEDg Description generation batch_69adeb8b3d2c8190b13c03ce944f436a completed March 8, 2026, 9:35 p.m.
NED2 Entity disambiguation (via description) batch_69adec123cc481908e55dfbe4f4da095 completed March 8, 2026, 9:37 p.m.
Created at: March 4, 2026, 7:35 p.m.