Triple
T31692545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Riding Hood (2011 film) |
E808829
|
entity |
| Predicate | marketingComparison |
P156221
|
FINISHED |
| Object | Twilight film series |
—
|
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: Twilight film series | Statement: [Red Riding Hood (2011 film), marketingComparison, Twilight film series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marketingComparison Context triple: [Red Riding Hood (2011 film), marketingComparison, Twilight film series]
-
A.
comparisonUses
Indicates that one entity employs another entity as a basis or tool for making a comparison.
-
B.
comparisonAspect
Indicates that two or more entities are being compared specifically with respect to a particular shared attribute or dimension.
-
C.
technologyComparableTo
Indicates that one technology can be meaningfully compared to another in terms of capability, performance, or relevant characteristics.
-
D.
comparisonReason
Indicates that one entity is being compared to another specifically due to a stated reason, motive, or basis for the comparison.
-
E.
comparisonUnit
chosen
Indicates that one entity serves as the reference or baseline unit against which another entity is compared or measured.
- 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_69f348ddcbc48190950cabcc25ff29b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 30, 2026, 11:09 p.m.