Triple
T34791448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King John's Christmas |
E1002956
|
entity |
| Predicate | literaryCharacterDescribedAs |
P115276
|
FINISHED |
| Object | greedy |
—
|
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: greedy | Statement: [King John's Christmas, literaryCharacterDescribedAs, greedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryCharacterDescribedAs Context triple: [King John's Christmas, literaryCharacterDescribedAs, greedy]
-
A.
literaryCharacterDepicted
Indicates that a literary character is visually or textually represented in a work such as an image, illustration, or other medium.
-
B.
literaryCharacterModeledAs
Indicates that one literary character is created or portrayed based on the traits, life, or persona of another real or fictional individual.
-
C.
characterInWorkDescribedAs
chosen
Indicates that a character is portrayed or described in a particular way within a specific work.
-
D.
characterDescription
Indicates that one entity provides a textual description or portrayal of the characteristics, traits, or attributes of another entity.
-
E.
filmCharacterDescribedAs
Indicates that a film character is described or characterized using a particular attribute, phrase, or depiction.
- 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_69f76db47d408190a24fc7164439ea2d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 3:59 p.m.