Triple
T25433558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kayles |
E637318
|
entity |
| Predicate | hasTeachingUse |
P27185
|
FINISHED |
| Object | example game in combinatorial game theory courses |
—
|
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: example game in combinatorial game theory courses | Statement: [Kayles, hasTeachingUse, example game in combinatorial game theory courses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTeachingUse Context triple: [Kayles, hasTeachingUse, example game in combinatorial game theory courses]
-
A.
hasEducationalUse
chosen
Indicates that something is intended to be used for educational or instructional purposes.
-
B.
usesInTeaching
Indicates that an agent employs a particular resource, method, or material as part of their teaching activities.
-
C.
hasTeachingMode
Indicates that an entity is associated with a particular method, style, or mode of teaching or instruction.
-
D.
containsTeachingOf
Indicates that one entity includes, embodies, or presents the teaching, doctrine, or instructional content associated with another entity.
-
E.
hasTeachingContext
Indicates that an entity is associated with a specific educational or instructional setting in which teaching occurs.
- 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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f63182f1408190bddc1214fcbd6145 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 21, 2026, 1:59 p.m.