Triple
T28772241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Saint-Lazare – western suburbs axis |
E726441
|
entity |
| Predicate | belongsToStationGroup |
P33789
|
FINISHED |
| Object | Paris Saint-Lazare rail lines |
—
|
NE NERFINISHED |
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: Paris Saint-Lazare rail lines | Statement: [Paris–Saint-Lazare – western suburbs axis, belongsToStationGroup, Paris Saint-Lazare rail lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToStationGroup Context triple: [Paris–Saint-Lazare – western suburbs axis, belongsToStationGroup, Paris Saint-Lazare rail lines]
-
A.
hasStationGroup
chosen
Indicates that an entity is associated with, or belongs to, a particular group or collection of stations.
-
B.
belongsToGroup
Indicates that an entity is a member of, or is included within, a particular group or collection.
-
C.
associatedWithStationName
Indicates a relationship where something is linked or connected to a particular station identified by its name.
-
D.
associatedWithStationRole
Indicates that an entity has a connection or involvement with a specific role or function at a station.
-
E.
associatedStationCategory
Indicates that one entity is linked to, or classified under, a particular category of station.
- 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_69f03199997c8190b6ae43fb19312443 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
Created at: April 28, 2026, 6:16 a.m.