Triple
T8457071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebbsfleet International |
E199944
|
entity |
| Predicate | distanceFromStPancrasInternational |
P71653
|
FINISHED |
| Object | about 17 minutes by high-speed train |
—
|
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 17 minutes by high-speed train | Statement: [Ebbsfleet International, distanceFromStPancrasInternational, about 17 minutes by high-speed train]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromStPancrasInternational Context triple: [Ebbsfleet International, distanceFromStPancrasInternational, about 17 minutes by high-speed train]
-
A.
distanceFromStPancras
chosen
Indicates the spatial distance between an entity and St Pancras.
-
B.
distanceFromParisSaintLazare
Indicates the physical distance between a given place and Paris Saint-Lazare railway station.
-
C.
distanceToDisneylandParis
Indicates the physical distance between a given location and Disneyland Paris.
-
D.
distanceFromParisCenter
Indicates the measured distance between a given location and the central point of Paris.
-
E.
distanceFromToronto
Indicates the spatial distance between a given entity and the location of Toronto.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe48f180c8190a71cf9d7248ade60 |
completed | March 31, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:10 p.m.