Triple
T4670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Academy of Engineering |
E91
|
entity |
| Predicate | topicOfAdvice |
P489
|
FINISHED |
| Object | engineering issues of national importance |
—
|
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: engineering issues of national importance | Statement: [National Academy of Engineering, topicOfAdvice, engineering issues of national importance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topicOfAdvice Context triple: [National Academy of Engineering, topicOfAdvice, engineering issues of national importance]
-
A.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
B.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
C.
parent
Indicates a relationship where one entity is the direct mother or father of another entity, from whom that other entity is descended.
-
D.
activity
Indicates that an entity is engaged in or performing a particular action, behavior, or process.
-
E.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23c24b3d08190a714126292fd5479 |
completed | Feb. 28, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69a23998af288190855f0456740cbd51 |
completed | Feb. 28, 2026, 12:40 a.m. |
| PDg | Predicate description generation | batch_69a23c23fef88190ba5d6d86acd4a66f |
completed | Feb. 28, 2026, 12:51 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.