Triple

T32018735
Position Surface form Disambiguated ID Type / Status
Subject Chaville-Vélizy station E817618 entity
Predicate partOf P40 FINISHED
Object Transilien Paris-Montparnasse sector
The Transilien Paris-Montparnasse sector is a suburban rail network operated by SNCF that serves commuter routes radiating from Paris-Montparnasse station to the southwestern suburbs and surrounding region.
E2011079 NE FINISHED

How this triple was built (2 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: Transilien Paris-Montparnasse sector | Statement: [Chaville-Vélizy station, partOf, Transilien Paris-Montparnasse sector]
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: Transilien Paris-Montparnasse sector
Triple: [Chaville-Vélizy station, partOf, Transilien Paris-Montparnasse sector]
Generated description
The Transilien Paris-Montparnasse sector is a suburban rail network operated by SNCF that serves commuter routes radiating from Paris-Montparnasse station to the southwestern suburbs and surrounding region.

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_69f348fb04e4819081f4eab040ed7959 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b462d42c8190af298000e2d9bbfe completed May 3, 2026, 2:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34703015988190842130e92024d920 completed June 18, 2026, 10:24 p.m.
NEDg Description generation batch_6a34746da0f08190b7668348948d1b78 completed June 18, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_6a34752cbca88190a23836df888e4e1a completed June 18, 2026, 10:46 p.m.
Created at: May 1, 2026, 12:16 a.m.