Triple
T17748441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marvel's Hit-Monkey |
E443045
|
entity |
| Predicate | featuresProtagonistSpecies |
P39813
|
FINISHED |
| Object | Japanese macaque |
—
|
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: Japanese macaque | Statement: [Marvel's Hit-Monkey, featuresProtagonistSpecies, Japanese macaque]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresProtagonistSpecies Context triple: [Marvel's Hit-Monkey, featuresProtagonistSpecies, Japanese macaque]
-
A.
protagonistSpecies
chosen
Indicates that an entity is the species or kind of creature to which the protagonist of a story or scenario belongs.
-
B.
associatedCharacterSpecies
Indicates that one entity is related to, or linked with, the species of a particular character.
-
C.
fictionalSpecies
Indicates that the subject is a species that exists only in fiction or imaginary works, rather than in real life.
-
D.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
-
E.
featuresCharacterWith
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47ad46a50819089c87f74efe3c7ca |
completed | April 19, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:10 a.m.