Triple
T26525131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney direct-to-video films |
E670665
|
entity |
| Predicate | contentCharacteristics |
P134574
|
FINISHED |
| Object | family-friendly |
—
|
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: family-friendly | Statement: [Disney direct-to-video films, contentCharacteristics, family-friendly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contentCharacteristics Context triple: [Disney direct-to-video films, contentCharacteristics, family-friendly]
-
A.
contentCharacterization
chosen
Indicates that one entity characterizes, describes, or classifies the content or informational nature of another entity.
-
B.
formatCharacteristics
Indicates how something is structured, arranged, or presented in terms of its format or layout.
-
C.
artCharacteristics
Indicates a relationship where specific qualities, styles, or features are attributed to a work of art.
-
D.
dataCharacteristic
Indicates that one entity specifies a property, attribute, or feature that characterizes a given piece of data.
-
E.
codeCharacteristic
Indicates that one piece of code possesses a specific property, feature, or quality in relation to another referenced aspect.
- 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_69eeb31ea1e08190b9ff43cf9bc25bf8 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 27, 2026, 1:31 a.m.