Triple
T14016380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nature Cat |
E337213
|
entity |
| Predicate | hasEducationalGenre |
P61666
|
FINISHED |
| Object | science education for children |
—
|
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: science education for children | Statement: [Nature Cat, hasEducationalGenre, science education for children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationalGenre Context triple: [Nature Cat, hasEducationalGenre, science education for children]
-
A.
educationalGenre
chosen
Indicates that one entity is categorized as an educational type or genre of content in relation to another entity.
-
B.
hasEducationalAudience
Indicates that something is intended for or directed toward a specific educational audience or learner group.
-
C.
hasEducationalDimension
Indicates that something includes, involves, or contributes to an educational aspect, purpose, or impact within the relationship or context described.
-
D.
hasEducationalFeature
Indicates that something includes or is associated with a component, characteristic, or functionality intended for educational purposes.
-
E.
hasEducationalUse
Indicates that something is intended to be used for educational or instructional purposes.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2f396b648190927e5718c3bb6511 |
completed | April 14, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69de05a802ac819090604025aae6a4d5 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:19 p.m.