Triple
T2191939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin the Dog |
E49880
|
entity |
| Predicate | fictionalCharacterType |
P20971
|
FINISHED |
| Object | anthropomorphic dog |
—
|
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: anthropomorphic dog | Statement: [Franklin the Dog, fictionalCharacterType, anthropomorphic dog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalCharacterType Context triple: [Franklin the Dog, fictionalCharacterType, anthropomorphic dog]
-
A.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
B.
notableCharacterType
chosen
Indicates that an entity is a notable or prominent example of a specified character type or role.
-
C.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
D.
isGivenNameOfFictionalCharacter
Indicates that a given name is the personal name borne by a fictional character.
-
E.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf48ceb48190956df39377df0548 |
completed | March 7, 2026, 6:01 a.m. |
| PD | Predicate disambiguation | batch_69abbda52328819089c7ab111bebb0ca |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.