Triple

T30320506
Position Surface form Disambiguated ID Type / Status
Subject MAN Lion’s City A47 E771184 entity
Predicate hasChassisFamily P192061 FINISHED
Object MAN Lion’s City chassis
The MAN Lion’s City chassis is a modular low-floor bus platform developed by MAN for use in urban and suburban public transport vehicles.
 E1910439 NE FINISHED

How this triple was built (3 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 chassis | Statement: [MAN Lion’s City A47, hasChassisFamily, MAN Lion’s City chassis]
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 chassis
Triple: [MAN Lion’s City A47, hasChassisFamily, MAN Lion’s City chassis]
Generated description
The MAN Lion’s City chassis is a modular low-floor bus platform developed by MAN for use in urban and suburban public transport vehicles.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasChassisFamily
Context triple: [MAN Lion’s City A47, hasChassisFamily, MAN Lion’s City chassis]
  • A. hasChassisType
    Indicates that an entity is associated with or equipped with a specific type of chassis.
  • B. supportsChassisType
    Indicates that one entity is compatible with and can be used to support or accommodate a specified chassis type.
  • C. chassisName
    Indicates the designated name or identifier assigned to a chassis in a system or dataset.
  • D. chassisFeature
    Indicates that a particular feature, component, or characteristic is part of or associated with a chassis.
  • E. chassisCode
    Indicates the specific chassis designation or code assigned to a vehicle model to distinguish its underlying structural platform or variant.
  • F. None of above. chosen

Provenance (7 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_69f22489ee8481909344649bfbb92e83 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69fcf36d2894819089b7db8e91b63c9d completed May 7, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a277c14c9688190b2a6875c39fca80a completed June 9, 2026, 2:36 a.m.
NEDg Description generation batch_6a277cefc06881909023e8a019d6395a completed June 9, 2026, 2:39 a.m.
NED2 Entity disambiguation (via description) batch_6a277dac3814819086f5f3efc1a79349 completed June 9, 2026, 2:42 a.m.
PD Predicate disambiguation batch_69fcf25c0a108190bfa823474098640b completed May 7, 2026, 8:13 p.m.
PDg Predicate description generation batch_69fcf36bb86c8190a0a0ccf47cb56e5c completed May 7, 2026, 8:17 p.m.
Created at: April 29, 2026, 7:52 p.m.