Triple
T7518187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marne-la-Vallée–Chessy station |
E177697
|
entity |
| Predicate | travelTimeToParisByRER |
P77431
|
FINISHED |
| Object | about 35–45 minutes |
—
|
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: about 35–45 minutes | Statement: [Marne-la-Vallée–Chessy station, travelTimeToParisByRER, about 35–45 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeToParisByRER Context triple: [Marne-la-Vallée–Chessy station, travelTimeToParisByRER, about 35–45 minutes]
-
A.
distanceFromParisSaintLazare
Indicates the physical distance between a given place and Paris Saint-Lazare railway station.
-
B.
distanceFromCalais
Indicates the measured distance separating a given place or object from the location of Calais.
-
C.
directionFromParis
Indicates the cardinal or relative compass direction of an entity as measured from Paris toward that entity.
-
D.
travelTimeByFerry
Indicates the duration required to travel between two locations specifically using a ferry as the mode of transportation.
-
E.
followingStationOnOrangeLine
Indicates that one station is the next station in sequence after another station on the Orange Line.
- 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_69c69f2891148190a484f3b8222c6f1b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5f850c081909e697219071293fc |
completed | March 27, 2026, 9:26 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d44e9481909813e073b194f6f4 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f574d8a8819095749518dad13791 |
completed | March 27, 2026, 9:24 p.m. |
Created at: March 27, 2026, 3:46 p.m.