Triple
T36737293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asclepiadean meter |
E907516
|
entity |
| Predicate | typicalLineLength |
P18065
|
FINISHED |
| Object | medium-length lyric line |
—
|
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: medium-length lyric line | Statement: [Asclepiadean meter, typicalLineLength, medium-length lyric line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLineLength Context triple: [Asclepiadean meter, typicalLineLength, medium-length lyric line]
-
A.
lineLengthType
Indicates the type or category used to characterize the length of a line.
-
B.
hasLineLength
Indicates that one entity has, is characterized by, or is associated with a specific line length value.
-
C.
typicalLength
chosen
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
D.
lineLengthServed
Indicates the length of a line that has been provided or delivered in a given context.
-
E.
supportsLineLengthControl
Indicates that an entity provides functionality to configure or enforce limits on the length of lines (e.g., in text or code).
- 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_69f76e75aa6881909b844d00a3888ee5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:12 p.m.