Triple

T19485134
Position Surface form Disambiguated ID Type / Status
Subject Lyon Metro E487491 entity
Predicate hasRollingStock P1305 FINISHED
Object MPL 14
MPL 14 is a modern rubber-tyred metro train model used on the Lyon Metro system in France.
E1378516 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: MPL 14 | Statement: [Lyon Metro, hasRollingStock, MPL 14]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MPL 14
Context triple: [Lyon Metro, hasRollingStock, MPL 14]
  • A. MPL 16
    MPL 16 is a modern automated rubber-tyred metro train used on Lyon’s Line B as part of the network’s upgraded driverless rolling stock.
  • B. MPL 85
    MPL 85 is a type of rubber-tyred, automated metro train used on Lyon’s Line D.
  • C. MPL
    MPL is the National Rail station code for Marple railway station in Greater Manchester, England.
  • D. MPL
    MPL (Mozilla Public License) is a free and open-source software license created by Mozilla that allows code to be shared and modified while requiring that changes to MPL-covered files remain publicly available.
  • E. MPL
    MPL is the IATA airport code for Montpellier-Méditerranée Airport, serving the city of Montpellier in southern 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: MPL 14
Triple: [Lyon Metro, hasRollingStock, MPL 14]
Generated description
MPL 14 is a modern rubber-tyred metro train model used on the Lyon Metro system in France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MPL 14
Target entity description: MPL 14 is a modern rubber-tyred metro train model used on the Lyon Metro system in France.
  • A. MPL 16
    MPL 16 is a modern automated rubber-tyred metro train used on Lyon’s Line B as part of the network’s upgraded driverless rolling stock.
  • B. MPL 85
    MPL 85 is a type of rubber-tyred, automated metro train used on Lyon’s Line D.
  • C. MPL
    MPL is the IATA airport code for Montpellier-Méditerranée Airport, serving the city of Montpellier in southern France.
  • D. MPL
    MPL (Mozilla Public License) is a free and open-source software license created by Mozilla that allows code to be shared and modified while requiring that changes to MPL-covered files remain publicly available.
  • E. MPL
    MPL is the National Rail station code for Marple railway station in Greater Manchester, England.
  • 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_69d8e8d924388190b847cb15bb3d0aff completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6343dcc748190b0df816e6ab4cafb completed April 20, 2026, 2:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a074059d9948190bb54e2df1713927b completed May 15, 2026, 3:48 p.m.
NEDg Description generation batch_6a07411bd900819099237aaee874411b completed May 15, 2026, 3:51 p.m.
NED2 Entity disambiguation (via description) batch_6a074197aa14819096a74aab7bca9e3c completed May 15, 2026, 3:53 p.m.
Created at: April 10, 2026, 1:39 p.m.