Triple
T2496795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Rail Class 397 |
E52168
|
entity |
| Predicate | numberInClass |
P39825
|
FINISHED |
| Object | 12 units (approximate) |
—
|
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: 12 units (approximate) | Statement: [British Rail Class 397, numberInClass, 12 units (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberInClass Context triple: [British Rail Class 397, numberInClass, 12 units (approximate)]
-
A.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
B.
currentNumberOfClasses
Indicates the present count of classes associated with or contained by a given entity.
-
C.
numberOfPersons
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
-
D.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
E.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1abd3688190b5874249e1e333bc |
completed | March 7, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1318f7881908a8fc42943df4879 |
completed | March 7, 2026, 7:18 a.m. |
Created at: March 6, 2026, 9:46 p.m.