Triple
T11287386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Métro Line 13 |
E267231
|
entity |
| Predicate | connectsToRER |
P65119
|
FINISHED |
| Object | RER C at Invalides |
—
|
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: RER C at Invalides | Statement: [Paris Métro Line 13, connectsToRER, RER C at Invalides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsToRER Context triple: [Paris Métro Line 13, connectsToRER, RER C at Invalides]
-
A.
connectsTo
Indicates a relationship where one entity is linked or joined to another, allowing interaction, communication, or transfer between them.
-
B.
connectsToRailStation
chosen
Indicates that one entity has a direct link, route, or access connection to a rail station.
-
C.
connectsToRailwayNetwork
Indicates that one entity is physically or functionally linked to a railway network, allowing access or transfer between them.
-
D.
hasFareGateConnectionTo
Indicates that there is a direct passage or connection between two areas that is controlled or mediated by fare gates.
-
E.
hasMajorRailLinksTo
Indicates that there are significant railway connections or routes between two locations.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e986b0f08190a414749eaa7f1a5d |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a240588190aa097298f951c915 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.