Triple
T18399111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anushtubh meter |
E449943
|
entity |
| Predicate | hasProsodicUnit |
P130969
|
FINISHED |
| Object | syllable |
—
|
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: syllable | Statement: [Anushtubh meter, hasProsodicUnit, syllable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProsodicUnit Context triple: [Anushtubh meter, hasProsodicUnit, syllable]
-
A.
hasProsodicType
Indicates that one entity is characterized by a particular prosodic pattern or category (such as stress, intonation, or rhythm type) in relation to another.
-
B.
hasPhoneme
Indicates that a linguistic unit (such as a word or morpheme) contains or includes a particular phoneme as part of its sound structure.
-
C.
hasPhonemicTone
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
-
D.
hasPhonemicVowels
Indicates that a language or linguistic system distinguishes vowel sounds as separate phonemes that can change word meaning.
-
E.
hasSyllabicStructure
Indicates that an entity possesses a specific arrangement or pattern of syllables, such as their number, order, or type.
- 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_69d8b9fab8a8819086a9ddc0871715e0 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e518499b1481909c5de786c48faeba |
completed | April 19, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69e44ff1f92c8190afbb8e85d12bf2a9 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a1bda48190a9cd1db436d4be62 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:46 a.m.