Triple
T29451757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Burmese Harp |
E746992
|
entity |
| Predicate | protagonistLaterRole |
P165917
|
FINISHED |
| Object | Buddhist monk |
—
|
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: Buddhist monk | Statement: [The Burmese Harp, protagonistLaterRole, Buddhist monk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistLaterRole Context triple: [The Burmese Harp, protagonistLaterRole, Buddhist monk]
-
A.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
B.
protagonistDescription
Indicates that a text provides a descriptive summary or characterization of the story’s main protagonist.
-
C.
protagonistAlterEgoOf
Indicates that one entity is the alternate identity or secret persona of the main character (protagonist) in a narrative.
-
D.
roleForProtagonist
chosen
Indicates the specific narrative or functional role that an entity plays in relation to the story’s main protagonist.
-
E.
laterMainCharacterOf
Indicates that one entity becomes the main character of a work at a later point in time, succeeding another main character.
- 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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 28, 2026, 3:33 p.m.