Triple
T16709887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How to Ride a Horse |
E406077
|
entity |
| Predicate | featuresTypeOfAnimation |
P96809
|
FINISHED |
| Object | traditional hand-drawn animation |
—
|
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: traditional hand-drawn animation | Statement: [How to Ride a Horse, featuresTypeOfAnimation, traditional hand-drawn animation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresTypeOfAnimation Context triple: [How to Ride a Horse, featuresTypeOfAnimation, traditional hand-drawn animation]
-
A.
featuresAnimation
chosen
Indicates that something includes or prominently presents an animation as part of its content or functionality.
-
B.
featuresCastType
Indicates that one entity includes or highlights a particular type or category of cast (e.g., actors or performers) associated with it.
-
C.
filmType
Indicates the specific category or genre that a film belongs to.
-
D.
genreFeatures
Indicates that a particular genre is characterized or defined by certain features or attributes.
-
E.
featuresFictionalProgram
Indicates that a work includes or presents a fictional program (such as a TV show, software, or in-universe broadcast) 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3865186b48190bb45a761f5cf1a83 |
completed | April 18, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:20 a.m.