Triple
T31924172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nottuswaras |
E815054
|
entity |
| Predicate | textMeterCharacteristic |
P134574
|
FINISHED |
| Object | mostly simple, regular metrical patterns |
—
|
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: mostly simple, regular metrical patterns | Statement: [Nottuswaras, textMeterCharacteristic, mostly simple, regular metrical patterns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textMeterCharacteristic Context triple: [Nottuswaras, textMeterCharacteristic, mostly simple, regular metrical patterns]
-
A.
formatCharacteristics
Indicates how something is structured, arranged, or presented in terms of its format or layout.
-
B.
contentCharacterization
chosen
Indicates that one entity characterizes, describes, or classifies the content or informational nature of another entity.
-
C.
textCharacter
Indicates that one entity is a character (such as a letter, digit, or symbol) within a piece of text associated with another entity.
-
D.
termCharacteristics
Indicates the defining properties, attributes, or features that characterize a given term.
-
E.
codeCharacteristic
Indicates that one piece of code possesses a specific property, feature, or quality in relation to another referenced aspect.
- 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_69f348f1df848190851bbfb988da3414 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b1fa05a081909ba84d0efc314ec4 |
completed | May 3, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69f6aca7081881909e96a8b05ec086bb |
completed | May 3, 2026, 2:02 a.m. |
Created at: May 1, 2026, 12:03 a.m.