Triple

T16723208
Position Surface form Disambiguated ID Type / Status
Subject Versailles-Rive-Gauche E406399 entity
Predicate fareZone P844 FINISHED
Object Zone 4
Zone 4 is one of the outer public transport fare zones in the Île-de-France region surrounding central Paris.
 E1231279 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 4 | Statement: [Versailles-Rive-Gauche, fareZone, Zone 4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zone 4
Context triple: [Versailles-Rive-Gauche, fareZone, Zone 4]
  • A. Zone 4
    Zone 4 is a suburban travel zone in London’s public transport fare system, covering outer residential areas served by the Underground, Overground, and National Rail services.
  • B. Zone 4
    Zone 4 is an American record label known for developing and promoting R&B and hip-hop artists, including singer-songwriter Keri Hilson.
  • C. Zone 5
    Zone 5 is an outer fare zone in the London public transport system used for calculating ticket and Travelcard prices.
  • D. 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.
  • E. Zone 3
    Zone 3 is one of the concentric public transport fare zones in the Île-de-France region surrounding central Paris.
  • 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 4
Triple: [Versailles-Rive-Gauche, fareZone, Zone 4]
Generated description
Zone 4 is one of the outer 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 4
Target entity description: Zone 4 is one of the outer public transport fare zones in the Île-de-France region surrounding central Paris.
  • A. Zone 4
    Zone 4 is a suburban travel zone in London’s public transport fare system, covering outer residential areas served by the Underground, Overground, and National Rail services.
  • B. Zone 4
    Zone 4 is an American record label known for developing and promoting R&B and hip-hop artists, including singer-songwriter Keri Hilson.
  • C. Zone 5
    Zone 5 is an outer fare zone in the London public transport system used for calculating ticket and Travelcard prices.
  • D. 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.
  • E. Zone 3
    Zone 3 is one of the concentric public transport fare zones in the Île-de-France region surrounding central Paris.
  • 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_69d8838f242881908abd8bc138795886 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e387449eb08190b174f8e142ea631b completed April 18, 2026, 1:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d43c49081908eca922da8f90793 completed May 10, 2026, 2:59 p.m.
NEDg Description generation batch_6a00a19d8dc08190be5d750f71b083dc completed May 10, 2026, 3:17 p.m.
NED2 Entity disambiguation (via description) batch_6a00a269cacc81909d084c5d3497a4e6 completed May 10, 2026, 3:21 p.m.
Created at: April 10, 2026, 5:20 a.m.