Triple
T2764203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Engineering Mathematics |
E61294
|
entity |
| Predicate | knowledgeArea |
P28568
|
FINISHED |
| Object | STEM education |
—
|
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: STEM education | Statement: [Engineering Mathematics, knowledgeArea, STEM education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knowledgeArea Context triple: [Engineering Mathematics, knowledgeArea, STEM education]
-
A.
knowledgeType
Indicates the specific category or nature of knowledge associated with an entity or statement (e.g., factual, procedural, conceptual).
-
B.
competenceArea
Indicates that one entity has a particular domain, field, or area in which it possesses competence, expertise, or responsibility.
-
C.
thematicArea
chosen
Indicates the subject or item is associated with, or falls under, a particular thematic area or topic of focus.
-
D.
knowledgeExchange
Indicates a reciprocal sharing or transfer of knowledge, information, or expertise between entities.
-
E.
keyIssueArea
Indicates that something is a primary topic, domain, or field that is central or especially important within a broader context or discussion.
- 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_69ab4b7bab6c8190a5c2efef19a8ef34 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdcfc5e1c8190a5ac2c48d3eaeb0a |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.