Triple
T5489135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jangnama |
E123656
|
entity |
| Predicate | typicalMeter |
P62937
|
FINISHED |
| Object | Punjabi folk verse |
—
|
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: Punjabi folk verse | Statement: [Jangnama, typicalMeter, Punjabi folk verse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMeter Context triple: [Jangnama, typicalMeter, Punjabi folk verse]
-
A.
typicalMeterInEnglish
Indicates that a given poetic meter is commonly or characteristically used in English verse.
-
B.
typicalMeterInItalian
Indicates that a given meter is the one most commonly or traditionally used in Italian for the specified context.
-
C.
dominantMetreOf
chosen
Indicates that one metre (rhythmic pattern) is the primary or prevailing metrical structure used in another work, passage, or musical/poetic context.
-
D.
choralMeter
Indicates a relationship where a musical work or passage is characterized by a specific metrical pattern typical of choral music.
-
E.
typicalFootCountPerHemistich
Indicates the usual number of metrical feet found in each hemistich (half-line) of a verse.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd93e5d0f08190a6cc9fc408b7c5bb |
completed | March 20, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69bd91a73b148190a865243536a4fe76 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:10 p.m.