Triple
T27992201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Achnacarry Commando Basic Training Centre |
E706908
|
entity |
| Predicate | approximateNumberOfTrainees |
P111137
|
FINISHED |
| Object | thousands of commandos |
—
|
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: thousands of commandos | Statement: [Achnacarry Commando Basic Training Centre, approximateNumberOfTrainees, thousands of commandos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfTrainees Context triple: [Achnacarry Commando Basic Training Centre, approximateNumberOfTrainees, thousands of commandos]
-
A.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
B.
hasApproximateNumberOfPeople
chosen
Indicates that an entity is associated with an estimated or approximate count of people, rather than an exact number.
-
C.
approximateCourseLength
Indicates an estimated or rough value for the length or duration of a course rather than an exact measurement.
-
D.
employsApproximateNumberOfPeople
Indicates that an entity employs a roughly estimated or approximate number of people, rather than an exact headcount.
-
E.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
- 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_69ef96b8b8d88190bad5e4ae966bf14e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: April 27, 2026, 7:50 p.m.