Triple
T3458249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hook, Hampshire |
E72958
|
entity |
| Predicate | travelTimeToLondonByTrain |
P39021
|
FINISHED |
| Object | about 1 hour |
—
|
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 1 hour | Statement: [Hook, Hampshire, travelTimeToLondonByTrain, about 1 hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeToLondonByTrain Context triple: [Hook, Hampshire, travelTimeToLondonByTrain, about 1 hour]
-
A.
timeToCentralLondonByTrain
chosen
Indicates the amount of time it takes to travel by train from a given location to central London.
-
B.
railwayTimeUsage
Indicates how much time is spent using or operating a railway within a given context or period.
-
C.
distanceToLondon
Indicates the measured distance between a given entity’s location and the city of London.
-
D.
approximateTravelTimeToVnukovo
Indicates the estimated duration it typically takes to travel from a given location to Vnukovo.
-
E.
approximateTravelTimeToDomodedovo
Indicates the estimated amount of time it typically takes to travel from a given location to Domodedovo.
- 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_69ad85b12a908190a1d10a6b03b4f8ae |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae36e748190bf20fd3c6de22e19 |
completed | March 8, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69adae041d588190a84a02bca94adec8 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:16 p.m.