Triple
T36236912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government Major Projects Portfolio |
E891399
|
entity |
| Predicate | assessmentScale |
P16725
|
FINISHED |
| Object | red |
—
|
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: red | Statement: [Government Major Projects Portfolio, assessmentScale, red]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: assessmentScale Context triple: [Government Major Projects Portfolio, assessmentScale, red]
-
A.
assessmentLevel
Indicates the degree, rating, or intensity assigned to an evaluation or judgment of something.
-
B.
scoreScale
chosen
Indicates the scale or range on which a score or rating is expressed or measured.
-
C.
assessment
Indicates an evaluation or judgment made about an entity’s quality, performance, or characteristics.
-
D.
assessmentEmphasis
Indicates the particular aspect, component, or criterion of a subject that an assessment is primarily focused on or gives greatest weight to.
-
E.
ratingContext
Indicates the situational or contextual factors under which a rating is given or applies.
- 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_69f76e4387048190a1b27bcbf4ec7423 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b5a727dc81908f5b1e5bb480101a |
completed | May 3, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c44390819084fb5558b354658f |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:09 p.m.