Triple
T29616576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master & Apprentice |
E754878
|
entity |
| Predicate | exploresCharacter |
P136307
|
FINISHED |
| Object | Qui-Gon Jinn’s views on the Living Force |
—
|
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: Qui-Gon Jinn’s views on the Living Force | Statement: [Master & Apprentice, exploresCharacter, Qui-Gon Jinn’s views on the Living Force]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exploresCharacter Context triple: [Master & Apprentice, exploresCharacter, Qui-Gon Jinn’s views on the Living Force]
-
A.
investigatesCharacter
Indicates that one entity conducts an inquiry or examination into another entity’s actions, background, or role.
-
B.
discussesCharacter
chosen
Indicates that one entity talks or writes about, analyzes, or otherwise addresses a particular character.
-
C.
plotCharacter
Indicates a relationship where a character plays a role or participates in the narrative plot of a story or work.
-
D.
featuresCharacterWith
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
E.
guidesCharacter
Indicates that one entity provides direction, advice, or mentorship to another entity (the character) in their actions or development.
- 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_69f0ef85f62081909842b59fdf8717e1 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 28, 2026, 6:31 p.m.