Triple
T35067974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Two Favorite People |
E1011782
|
entity |
| Predicate | narrativeRoleOfLadyRainicorn |
P83930
|
FINISHED |
| Object | supporting character |
—
|
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: supporting character | Statement: [My Two Favorite People, narrativeRoleOfLadyRainicorn, supporting character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrativeRoleOfLadyRainicorn Context triple: [My Two Favorite People, narrativeRoleOfLadyRainicorn, supporting character]
-
A.
protagonistHorse
Indicates that the subject is the main or central horse character in a narrative or story.
-
B.
narrativeRoleInSeries
chosen
Indicates the specific narrative function or role an entity plays within a particular series or serialized work.
-
C.
roleInStories
Indicates the specific function, position, or character part an entity plays within one or more stories.
-
D.
roleInPokémonTheFirstMovie
Indicates that an entity has a specific role or appearance in the film "Pokémon: The First Movie."
-
E.
narrativeCharacter
Indicates that one entity functions as a character within the narrative or story associated with another entity.
- 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_69f76dd193108190af2528186f25b72a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
Created at: May 3, 2026, 4:01 p.m.