Triple
T16193260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prophet Yusuf |
E392994
|
entity |
| Predicate | storyCharacterizedAs |
P122100
|
FINISHED |
| Object | best of stories |
—
|
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: best of stories | Statement: [Prophet Yusuf, storyCharacterizedAs, best of stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyCharacterizedAs Context triple: [Prophet Yusuf, storyCharacterizedAs, best of stories]
-
A.
narrativeCharacter
Indicates that one entity functions as a character within the narrative or story associated with another entity.
-
B.
plotCharacter
Indicates a relationship where a character plays a role or participates in the narrative plot of a story or work.
-
C.
characters
Indicates that one entity is a character (or set of characters) associated with, appearing in, or belonging to another entity (such as a work, story, or medium).
-
D.
characterSetting
Indicates that a character is associated with, appears in, or is situated within a particular setting or environment.
-
E.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222d74d788190a637fdb9b4f184b9 |
completed | April 17, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69e219e11f6081909106b1240a17fd37 |
completed | April 17, 2026, 11:30 a.m. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:02 a.m.