Triple

T27831864
Position Surface form Disambiguated ID Type / Status
Subject Noisy–Champs station E703122 entity
Predicate futureLine P41765 FINISHED
Object Paris Métro Line 16
Paris Métro Line 16 is a planned automated metro line in the Grand Paris Express network intended to serve northeastern suburbs of Paris with improved high-capacity transit connections.
 E1811001 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: Paris Métro Line 16 | Statement: [Noisy–Champs station, futureLine, Paris Métro Line 16]
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: Paris Métro Line 16
Triple: [Noisy–Champs station, futureLine, Paris Métro Line 16]
Generated description
Paris Métro Line 16 is a planned automated metro line in the Grand Paris Express network intended to serve northeastern suburbs of Paris with improved high-capacity transit connections.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: futureLine
Context triple: [Noisy–Champs station, futureLine, Paris Métro Line 16]
  • A. futureServes
    Indicates that, at a future time, one entity will perform a service or act in a serving role for another entity.
  • B. futureComponentOf
    Indicates that one entity is expected or planned to become a component or part of another entity at some point in the future.
  • C. futureEvolution
    Indicates a predicted or potential future development or transformation of one entity into another.
  • D. futurePosition
    Indicates that one entity will occupy or hold the position, role, or location of another entity at a later point in time.
  • E. futureSiteOf chosen
    Indicates that a location is planned or designated to become the site of a particular entity or structure in the future.
  • F. None of above.

Provenance (6 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_69ef840b94b08190950a4f77296938b2 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f63fd6c68481908c542aa03e297b9c completed May 2, 2026, 6:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1606f307e48190ba96189a2a044976 completed May 26, 2026, 8:47 p.m.
NEDg Description generation batch_6a161461afac81909c4f6f35530f73de completed May 26, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_6a161524fd648190b932ebe251413aa3 completed May 26, 2026, 9:48 p.m.
PD Predicate disambiguation batch_69f63c6895f0819088655277e45859a8 completed May 2, 2026, 6:03 p.m.
Created at: April 27, 2026, 5:56 p.m.