Triple
T17082670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porte de Saint-Ouen |
E414512
|
entity |
| Predicate | hasStationCodeRATP |
P1289
|
FINISHED |
| Object | 13-07 |
—
|
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: 13-07 | Statement: [Porte de Saint-Ouen, hasStationCodeRATP, 13-07]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationCodeRATP Context triple: [Porte de Saint-Ouen, hasStationCodeRATP, 13-07]
-
A.
hasStationCode
chosen
Indicates that an entity is associated with a specific station identification code.
-
B.
isPassengerStationCode
Indicates that a given code is officially assigned to identify a particular passenger station.
-
C.
servedByTransilienLine
Indicates that a location or facility is connected to and receives service from a specific Transilien railway line.
-
D.
isTransportationHubCodeFor
Indicates that a given code uniquely identifies and represents a specific transportation hub, such as a station, airport, or terminal.
-
E.
hasStationCodeSystem
Indicates that an entity uses or is associated with a particular system for assigning or managing station codes.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbe408d48190b4f52c2102eae7c2 |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d67b14481909fcdbdeaa5c34785 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.