Triple
T7794875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Explorers Hotel at Disneyland Paris |
E180273
|
entity |
| Predicate | distanceToDisneylandParis |
P79066
|
FINISHED |
| Object | approximately 10 minutes by shuttle |
—
|
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: approximately 10 minutes by shuttle | Statement: [Explorers Hotel at Disneyland Paris, distanceToDisneylandParis, approximately 10 minutes by shuttle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToDisneylandParis Context triple: [Explorers Hotel at Disneyland Paris, distanceToDisneylandParis, approximately 10 minutes by shuttle]
-
A.
distanceFromParisSaintLazare
Indicates the physical distance between a given place and Paris Saint-Lazare railway station.
-
B.
distanceToFrance
Indicates the spatial distance between a given entity and the country of France.
-
C.
distanceToCharlesDeGaulleAirport
Indicates the measured distance between a given location and Charles de Gaulle Airport.
-
D.
distanceFromParisCenter
Indicates the measured distance between a given location and the central point of Paris.
-
E.
distanceFromStPancras
Indicates the spatial distance between an entity and St Pancras.
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:31 p.m.