Triple
T29820174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurban Said |
E757222
|
entity |
| Predicate | workMainCharacters |
P39597
|
FINISHED |
| Object | Ali Khan Shirvanshir |
—
|
NE NERFINISHED |
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: Ali Khan Shirvanshir | Statement: [Kurban Said, workMainCharacters, Ali Khan Shirvanshir]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workMainCharacters Context triple: [Kurban Said, workMainCharacters, Ali Khan Shirvanshir]
-
A.
mainCharactersAre
chosen
Indicates that the specified entities serve as the primary or central characters in a narrative or work.
-
B.
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).
-
C.
hasMainCharacterFrom
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
D.
laterMainCharacterOf
Indicates that one entity becomes the main character of a work at a later point in time, succeeding another main character.
-
E.
associatedCharacters
Indicates that two or more characters are linked or connected through some relationship, involvement, or relevance to each other.
- 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_69f2245701c88190ad42415a0956c4ed |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6756645d48190a1645d578759dccd |
completed | May 2, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:28 p.m.