Triple
T27389085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Villetaneuse |
E691468
|
entity |
| Predicate | hasPublicTransportLinkTo |
P3791
|
FINISHED |
| Object | Saint-Denis |
—
|
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: Saint-Denis | Statement: [Villetaneuse, hasPublicTransportLinkTo, Saint-Denis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPublicTransportLinkTo Context triple: [Villetaneuse, hasPublicTransportLinkTo, Saint-Denis]
-
A.
hasPublicTransportConnection
chosen
Indicates that there is an available public transportation link or service connecting the related entities.
-
B.
hasPublicTransitNode
Indicates that there exists a public transportation stop, station, or node associated with or located at the referenced entity.
-
C.
hasPublicTransitRoute
Indicates that there exists a public transportation route (such as a bus, train, or tram line) connecting or serving the related entities.
-
D.
hasPublicTransportStop
Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
-
E.
accessibleByPublicTransport
Indicates that a location or entity can be reached using public transportation services such as buses, trains, or trams.
- 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_69ef520386788190bc92cfcd97ebb67a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 27, 2026, 12:25 p.m.