Triple
T25370945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vitry-sur-Seine |
E632928
|
entity |
| Predicate | hasPlannedTransportConnection |
P164982
|
FINISHED |
| Object | Paris Metro Line 15 |
—
|
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 Metro Line 15 | Statement: [Vitry-sur-Seine, hasPlannedTransportConnection, Paris Metro Line 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlannedTransportConnection Context triple: [Vitry-sur-Seine, hasPlannedTransportConnection, Paris Metro Line 15]
-
A.
plannedTransit
Indicates that a transit or trip has been scheduled or arranged to occur, but has not yet taken place.
-
B.
plannedToConnectCity
Indicates that an entity had the intention or made arrangements to establish a connection or link between cities.
-
C.
hasPassengerTransfers
Indicates that passengers move or are transferred from one vehicle, route, or segment of a journey to another.
-
D.
hasDepartureTo
Indicates that a departure event originates from one place and is directed toward a specific destination.
-
E.
hasPlannedTrain
Indicates that an entity is associated with a train that is scheduled or planned to operate, rather than one currently in service.
- F. None of above. chosen
Provenance (4 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_69e75a90c0dc819092f928b6ea0ecc72 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 21, 2026, 1:38 p.m.