Triple
T3818706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Glover as Lando Calrissian |
E84318
|
entity |
| Predicate | characterSkill |
P37384
|
FINISHED |
| Object | card playing |
—
|
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: card playing | Statement: [Donald Glover as Lando Calrissian, characterSkill, card playing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterSkill Context triple: [Donald Glover as Lando Calrissian, characterSkill, card playing]
-
A.
hasSupportingCharacterTrait
Indicates that a supporting character possesses a particular trait, quality, or characteristic.
-
B.
skillEmphasis
Indicates that a particular skill is given special focus, priority, or importance within a context such as a role, task, or curriculum.
-
C.
associatedCharacterTrait
chosen
Indicates a relationship where a character is linked to, or described by, a particular trait or quality.
-
D.
kills
Indicates that one entity causes the death of another entity, ending its life.
-
E.
developmentCharacter
Indicates a relationship where one entity contributes to or influences the growth, formation, or evolution of another entity’s characteristics or qualities.
- 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee74a2bc081909b237df8b1e27653 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.