Triple
T4857120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hassan |
E108562
|
entity |
| Predicate | literaryFormOfWork |
P6480
|
FINISHED |
| Object | 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: verse | Statement: [Hassan, literaryFormOfWork, verse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryFormOfWork Context triple: [Hassan, literaryFormOfWork, verse]
-
A.
literaryGenreOfWork
Indicates that a work belongs to or is classified under a particular literary genre.
-
B.
hasLiteraryForm
chosen
Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
-
C.
literaryUnit
Indicates that one entity is a distinct segment or component (such as a chapter, scene, or passage) within a larger literary work or text.
-
D.
literaryCollection
Indicates that one entity is a collection or compilation of literary works that includes or is associated with the other entity.
-
E.
literaryWorkInStory
Indicates that one literary work is referenced, featured, or embedded within the narrative of another story.
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2557388190a2d15571bacd24f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.