Triple
T32084981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaylee Hottle |
E819414
|
entity |
| Predicate | fictionalCreatureInteractedWithOnScreen |
P195146
|
FINISHED |
| Object | King Kong |
—
|
NE NERFINISHED |
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: King Kong | Statement: [Kaylee Hottle, fictionalCreatureInteractedWithOnScreen, King Kong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalCreatureInteractedWithOnScreen Context triple: [Kaylee Hottle, fictionalCreatureInteractedWithOnScreen, King Kong]
-
A.
usesCreature
Indicates that one entity employs, controls, or relies on a creature to perform an action or fulfill a function.
-
B.
mentionsCreature
Indicates that one entity refers to or brings up a particular creature in some form of communication or content.
-
C.
fictionalSpecies
Indicates that the subject is a species that exists only in fiction or imaginary works, rather than in real life.
-
D.
nonHumanCharacter
Indicates that the character involved in the relation is not a human being (e.g., an animal, creature, AI, or other non-human entity).
-
E.
animalProtagonist
Indicates that the main character or central figure in a narrative is an animal.
- F. None of above. chosen
Provenance (4 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fda94697c4819081291967202248be |
completed | May 8, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_69fda5973fcc8190a57daef31fb70a49 |
completed | May 8, 2026, 8:57 a.m. |
| PDg | Predicate description generation | batch_69fda945e1e08190bf923fcd4d2c548a |
completed | May 8, 2026, 9:13 a.m. |
Created at: May 1, 2026, 12:24 a.m.