Triple
T29165503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wings & Co. (Fairy Detective Agency) |
E739306
|
entity |
| Predicate | protagonistsAre |
P20969
|
FINISHED |
| Object | fairies |
—
|
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: fairies | Statement: [Wings & Co. (Fairy Detective Agency), protagonistsAre, fairies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistsAre Context triple: [Wings & Co. (Fairy Detective Agency), protagonistsAre, fairies]
-
A.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
B.
hasHumanProtagonists
Indicates that the primary characters driving the narrative are human beings rather than non-human entities.
-
C.
protagonistCount
Indicates the number of primary protagonists involved in a given narrative or work.
-
D.
protagonistBasedOn
Indicates that a fictional work’s main character is modeled on, inspired by, or derived from a particular real or fictional person or entity.
-
E.
protagonistType
chosen
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
- 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_69f07cb528fc8190a556b73990c347c8 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f67f7efc3c8190986d2d95b7a23729 |
completed | May 2, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 28, 2026, 11:49 a.m.