Triple
T15130269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gertie the Dinosaur |
E361399
|
entity |
| Predicate | animationFrameCount |
P62360
|
FINISHED |
| Object | approximately 10,000 drawings |
—
|
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: approximately 10,000 drawings | Statement: [Gertie the Dinosaur, animationFrameCount, approximately 10,000 drawings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: animationFrameCount Context triple: [Gertie the Dinosaur, animationFrameCount, approximately 10,000 drawings]
-
A.
frameDuration
Indicates the length of time that a single frame in a sequence (such as video or animation) is displayed before advancing to the next frame.
-
B.
numberOfStills
chosen
Indicates the quantity of still images associated with or contained in a given entity or context.
-
C.
movementCount
Indicates the number of times a movement or relocation action has occurred between the related entities.
-
D.
filmStripCount
Indicates the number of film strips associated with or contained in a given entity or context.
-
E.
hasAnimatedSequences
Indicates that the subject contains or includes one or more animated sequences.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b194748190801e3956bf2429d4 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:06 a.m.