Triple
T9060784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nutcracker Prince |
E217114
|
entity |
| Predicate | oftenPortrayedBy |
P18297
|
FINISHED |
| Object | male ballet dancer |
—
|
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: male ballet dancer | Statement: [Nutcracker Prince, oftenPortrayedBy, male ballet dancer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenPortrayedBy Context triple: [Nutcracker Prince, oftenPortrayedBy, male ballet dancer]
-
A.
wasPortrayedAs
Indicates that one entity has been depicted or represented in the form or role of another entity, typically within some medium or context.
-
B.
oftenDepictedAs
chosen
Indicates that one entity is frequently represented or portrayed in the form, appearance, or symbolism of another entity.
-
C.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
D.
portrayedAsFrom
Indicates that one entity is depicted or represented as originating from, or belonging to, the place or source specified by another entity.
-
E.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
- 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_69ca83d4425481909a319dab847724ec |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7ecbb1e88190acdbfccdd975fac1 |
completed | April 1, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee6d83c819095d8ed0779aa8511 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:11 p.m.