Triple
T19168337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sharktopus vs. Whalewolf |
E469244
|
entity |
| Predicate | hasFictionalCreatureType |
P15758
|
FINISHED |
| Object | chimeric monster |
—
|
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: chimeric monster | Statement: [Sharktopus vs. Whalewolf, hasFictionalCreatureType, chimeric monster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalCreatureType Context triple: [Sharktopus vs. Whalewolf, hasFictionalCreatureType, chimeric monster]
-
A.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
B.
hasFictionalInhabitants
Indicates that a place or setting is inhabited by fictional or imaginary beings.
-
C.
fictionalSpecies
chosen
Indicates that the subject is a species that exists only in fiction or imaginary works, rather than in real life.
-
D.
fictionalPerformerSpecies
Indicates that a performer in a fictional work belongs to, or is characterized as, a particular fictional species.
-
E.
associatedCharacterSpecies
Indicates that one entity is related to, or linked with, the species of a particular character.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f16132e081908c6b8d576163316e |
completed | April 20, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b83d6881908e6271c620f74100 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.