Triple
T300146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aqua |
E6178
|
entity |
| Predicate | notableCriticism |
P805
|
FINISHED |
| Object | overuse of gloss and transparency |
—
|
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: overuse of gloss and transparency | Statement: [Aqua, notableCriticism, overuse of gloss and transparency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCriticism Context triple: [Aqua, notableCriticism, overuse of gloss and transparency]
-
A.
hasCriticism
Indicates that one entity expresses disapproval, objection, or negative evaluation directed toward another entity.
-
B.
criticizedFor
chosen
Indicates that one entity expresses disapproval or negative judgment of another entity specifically because of a particular action, quality, or outcome.
-
C.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
D.
notableDuring
Indicates that something was especially prominent, active, or significant during a particular time period or event.
-
E.
criticalReception
Indicates how a work, performance, or product is evaluated and responded to by critics or professional reviewers.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93aff048190a633c8ae2b76a41f |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.