Triple
T19975047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ikue Ōtani |
E493666
|
entity |
| Predicate | hasNotableCharacterType |
P10724
|
FINISHED |
| Object | mascot characters |
—
|
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: mascot characters | Statement: [Ikue Ōtani, hasNotableCharacterType, mascot characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableCharacterType Context triple: [Ikue Ōtani, hasNotableCharacterType, mascot characters]
-
A.
hasHumanCharacters
Indicates that the subject includes or features characters that are human beings.
-
B.
hasCharacters
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
-
C.
hasNotableType
Indicates that an entity is associated with a specific notable category or type that characterizes its significance or role.
-
D.
hasTypicalCharacterType
chosen
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
-
E.
hasNotableGroupCharacteristic
Indicates that a group possesses a distinctive or noteworthy characteristic that sets it apart from other groups.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65bcca5088190b523584d11799400 |
completed | April 20, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69e537fae79c81909eae39500766d0b6 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:24 p.m.