Triple
T37553103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valley of Wisdom |
E933632
|
entity |
| Predicate | hasTypeOfTrainers |
P24513
|
FINISHED |
| Object | class trainers |
—
|
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: class trainers | Statement: [Valley of Wisdom, hasTypeOfTrainers, class trainers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfTrainers Context triple: [Valley of Wisdom, hasTypeOfTrainers, class trainers]
-
A.
hasClassTrainersFor
Indicates that an entity provides or is associated with trainers responsible for conducting or leading a particular class.
-
B.
hasClassTrainers
Indicates that a class or course is associated with one or more trainers responsible for conducting or leading it.
-
C.
hasTrainingType
chosen
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
D.
alsoTrains
Indicates that an entity, in addition to its primary role or activity, is involved in training another entity.
-
E.
hasOnScreenTrainer
Indicates that an entity has a trainer or instructor who appears on screen (e.g., in a video or broadcast) providing guidance or instruction.
- 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_69f76eca55bc8190acf25741793d5dac |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffe613c03481909f3043ec8bf0bed9 |
completed | May 10, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69ffe4a73fb4819091600725a443981a |
completed | May 10, 2026, 1:51 a.m. |
Created at: May 3, 2026, 4:17 p.m.