Triple
T35014627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peppermint Butler |
E1010018
|
entity |
| Predicate | roleInCandyKingdom |
P203086
|
FINISHED |
| Object | royal servant |
—
|
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: royal servant | Statement: [Peppermint Butler, roleInCandyKingdom, royal servant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInCandyKingdom Context triple: [Peppermint Butler, roleInCandyKingdom, royal servant]
-
A.
roleInDonkeyKongCountry
Indicates the specific role or function an entity has within the context of Donkey Kong Country.
-
B.
roleInKirbySuperStar
Indicates the specific function or part an entity plays within the context of the game *Kirby Super Star*.
-
C.
roleAtLuckyChap
Indicates that an entity holds or held a specific role or position at the organization LuckyChap.
-
D.
roleInDonkeyKong64
Indicates the role or function an entity has within the context of the game Donkey Kong 64.
-
E.
roleInCoco
Indicates that an entity serves a specific role or function within the context of the COCO dataset or framework.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a011e5a419081908d06a07b395ebd97 |
completed | May 11, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_6a011de119048190b27d361cffabc228 |
completed | May 11, 2026, 12:08 a.m. |
| PDg | Predicate description generation | batch_6a011e599cd081909687a314f8d1895b |
completed | May 11, 2026, 12:10 a.m. |
Created at: May 3, 2026, 4:01 p.m.