Triple
T29616575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master & Apprentice |
E754878
|
entity |
| Predicate | hasNotableCharacterDynamic |
P201182
|
FINISHED |
| Object | conflict between Qui-Gon Jinn and Obi-Wan Kenobi |
—
|
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: conflict between Qui-Gon Jinn and Obi-Wan Kenobi | Statement: [Master & Apprentice, hasNotableCharacterDynamic, conflict between Qui-Gon Jinn and Obi-Wan Kenobi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableCharacterDynamic Context triple: [Master & Apprentice, hasNotableCharacterDynamic, conflict between Qui-Gon Jinn and Obi-Wan Kenobi]
-
A.
hasNotableHero
Indicates that an entity is associated with a particularly distinguished or prominent hero.
-
B.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
C.
hasEnigmaticCharacter
Indicates that something possesses a mysterious, puzzling, or difficult-to-interpret quality or nature.
-
D.
hasHumanCharacters
Indicates that the subject includes or features characters that are human beings.
-
E.
doesNotFeatureCharacterDirectly
Indicates that the subject work does not include the specified character as an on-screen, on-page, or otherwise directly appearing participant in its content.
- F. None of above. chosen
Provenance (4 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_69ffdd05d1908190957deb11392f4595 |
completed | May 10, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69ffdc0d33c881908b3483bee8a96540 |
completed | May 10, 2026, 1:14 a.m. |
| PDg | Predicate description generation | batch_69ffdd0486e08190a0f2ff4ce0aee13b |
completed | May 10, 2026, 1:19 a.m. |
Created at: April 28, 2026, 6:31 p.m.