Triple

T8432384
Position Surface form Disambiguated ID Type / Status
Subject Bobigny–Pantin–Raymond Queneau E199144 entity
Predicate fareZone P844 FINISHED
Object Zone 3
Zone 3 is one of the concentric public transport fare zones in the Île-de-France region surrounding central Paris.
 E733980 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: Zone 3 | Statement: [Bobigny–Pantin–Raymond Queneau, fareZone, Zone 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zone 3
Context triple: [Bobigny–Pantin–Raymond Queneau, fareZone, Zone 3]
  • A. Zone 3
    Zone 3 is one of the MBTA Commuter Rail’s outer fare zones used to set ticket prices for trips between Boston and its surrounding suburbs.
  • B. Zone 5
    Zone 5 is an outer fare zone in the London public transport system used for calculating ticket and Travelcard prices.
  • C. Zone 1
    Zone 1 is the central London public transport fare zone that covers the city’s main commercial, tourist, and historic areas.
  • D. Zone 12
    Zone 12 is an outer Long Island Rail Road fare zone used for setting ticket prices to and from stations such as Mastic–Shirley.
  • E. Zona A
    Zona A was the Allied-administered western sector of the Free Territory of Trieste, encompassing the city of Trieste and surrounding areas after World War II.
  • 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: Zone 3
Triple: [Bobigny–Pantin–Raymond Queneau, fareZone, Zone 3]
Generated description
Zone 3 is one of the concentric public transport fare zones in the Île-de-France region surrounding central Paris.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zone 3
Target entity description: Zone 3 is one of the concentric public transport fare zones in the Île-de-France region surrounding central Paris.
  • A. Zone 3
    Zone 3 is one of the MBTA Commuter Rail’s outer fare zones used to set ticket prices for trips between Boston and its surrounding suburbs.
  • B. Zone 5
    Zone 5 is an outer fare zone in the London public transport system used for calculating ticket and Travelcard prices.
  • C. Zone 1
    Zone 1 is the central London public transport fare zone that covers the city’s main commercial, tourist, and historic areas.
  • D. Zone 12
    Zone 12 is an outer Long Island Rail Road fare zone used for setting ticket prices to and from stations such as Mastic–Shirley.
  • E. Zona A
    Zona A was the Allied-administered western sector of the Free Territory of Trieste, encompassing the city of Trieste and surrounding areas after World War II.
  • 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_69ca8313c99081909a5c6d83b91de5b3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbd1a5d7488190842e246444fc9a4e completed March 31, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d673ed48190abf765c203ed2a0f completed April 2, 2026, 7:40 a.m.
NEDg Description generation batch_69ce1e6e83008190a4c2f796928882c1 completed April 2, 2026, 7:44 a.m.
NED2 Entity disambiguation (via description) batch_69ce1f3d46f48190be7b494e808a70f9 completed April 2, 2026, 7:48 a.m.
Created at: March 30, 2026, 6:07 p.m.