Triple
T29940837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porte Maillot (Paris Métro) |
E760492
|
entity |
| Predicate | partOfAutomationProject |
P840
|
FINISHED |
| Object | Line 1 automation |
—
|
LITERAL 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: Line 1 automation | Statement: [Porte Maillot (Paris Métro), partOfAutomationProject, Line 1 automation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfAutomationProject Context triple: [Porte Maillot (Paris Métro), partOfAutomationProject, Line 1 automation]
-
A.
automatedIn
Indicates that an action, process, or operation is performed automatically within or by a specified system, context, or environment.
-
B.
partOfSystem
chosen
Indicates that one entity functions as a component or subsystem within the structure or organization of another entity.
-
C.
partOfProcess
Indicates that one event, step, or action occurs as a component or stage within a larger overall process.
-
D.
automatedBy
Indicates that an action, process, or function is carried out or controlled by an automated system or mechanism.
-
E.
automationType
Indicates the specific kind or category of automation applied or associated with an entity or process.
- F. None of above.
Provenance (3 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_69f22463f3648190a603c3ff305c660b |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fed09a12648190affcd9bacf7ca275 |
completed | May 9, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69fecf91d6f481908deb60c965c433ed |
completed | May 9, 2026, 6:09 a.m. |
Created at: April 29, 2026, 6:22 p.m.