Triple
T8137558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Road Services |
E190008
|
entity |
| Predicate | peakFleetSize |
P1848
|
FINISHED |
| Object | tens of thousands of vehicles |
—
|
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: tens of thousands of vehicles | Statement: [British Road Services, peakFleetSize, tens of thousands of vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakFleetSize Context triple: [British Road Services, peakFleetSize, tens of thousands of vehicles]
-
A.
peakUse
Indicates the time, condition, or context in which something reaches its maximum level of use or intensity.
-
B.
petitionSize
Indicates the number of signatures or participants associated with a given petition.
-
C.
peakStatus
Indicates the condition or phase of something at its highest or most intense point in its progression or lifecycle.
-
D.
fleetSize
chosen
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet associated with an entity.
-
E.
peakDayAttendance
Indicates the number of attendees present on the single highest-attendance day within a given period or event.
- 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_69ca82bd9900819099477cdc2eb4244f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4402b35c81909363ffa9ce952ca4 |
completed | March 31, 2026, 3:48 a.m. |
| PD | Predicate disambiguation | batch_69cb369c0d0481908762c488d7f77e74 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:35 p.m.