Triple
T16798972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daraza |
E408304
|
entity |
| Predicate | hasPoeticHeritage |
P104239
|
FINISHED |
| Object | Sindhi Sufi poetry |
—
|
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: Sindhi Sufi poetry | Statement: [Daraza, hasPoeticHeritage, Sindhi Sufi poetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoeticHeritage Context triple: [Daraza, hasPoeticHeritage, Sindhi Sufi poetry]
-
A.
hasPoeticLyrics
Indicates that something (such as a song, text, or speech) contains lyrics or wording that are artistic, expressive, or characteristic of poetry.
-
B.
hasPoeticEpigraphs
Indicates that one entity (typically a work) includes poetic epigraphs associated with or prefacing another entity.
-
C.
hasAncientLiteraryTradition
Indicates that an entity possesses a long-established, historically significant body of written literature originating in ancient times.
-
D.
hasPoeticVoice
chosen
Indicates that one entity possesses or exhibits the distinctive poetic style, tone, or expressive voice associated with another entity.
-
E.
hasRichOralTradition
Indicates that an entity is associated with a longstanding, culturally significant body of stories, histories, or knowledge transmitted primarily through spoken word rather than written texts.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2abc430819080c1303eded5f416 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319d0fdb8819088425bd82431640f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.