Triple
T2591406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autumn Rhythm (Number 30) |
E58128
|
entity |
| Predicate | hasNoConventionalSubject |
P40588
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Autumn Rhythm (Number 30), hasNoConventionalSubject, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoConventionalSubject Context triple: [Autumn Rhythm (Number 30), hasNoConventionalSubject, true]
-
A.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
-
B.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
C.
hasSubjectPronouns
Indicates that an entity is associated with one or more pronouns that function as its grammatical subject in sentences.
-
D.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
E.
hasNoIndefiniteArticle
Indicates that the related entity is expressed without an indefinite article (such as “a” or “an”) in the given linguistic context.
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd40075f08190b760cb41c1417169 |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d19308819089ee942513d567a4 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd37ef248819090ab6b86b67e355f |
completed | March 7, 2026, 7:27 a.m. |
Created at: March 6, 2026, 9:49 p.m.