Triple
T3313549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Hundred and One Dalmatians |
E69627
|
entity |
| Predicate | numberInDisneyAnimatedCanon |
P30077
|
FINISHED |
| Object | 17 |
—
|
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: 17 | Statement: [One Hundred and One Dalmatians, numberInDisneyAnimatedCanon, 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberInDisneyAnimatedCanon Context triple: [One Hundred and One Dalmatians, numberInDisneyAnimatedCanon, 17]
-
A.
disneyAnimatedFeatureNumber
chosen
Indicates the ordinal number assigned to a film within the sequence of Disney animated feature productions.
-
B.
filmNumberInStudioCanon
Indicates the ordinal position a film holds within a studio’s official canon or main sequence of releases.
-
C.
numberOfFilmsAppearedIn
Indicates the total count of distinct films in which a given entity has appeared.
-
D.
numberOfAnimals
Indicates the quantity of animals associated with a given entity or context.
-
E.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
- 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_69ad85a0bb048190a5458d2738012d61 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0ef548481908b3aabc7052c70d8 |
completed | March 8, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69ada4282730819092aa39c5f9269df0 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.