Triple
T14730753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Utter |
E346065
|
entity |
| Predicate | genreOfFictionalPortrayal |
P21332
|
FINISHED |
| Object | Western television series |
—
|
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: Western television series | Statement: [Charlie Utter, genreOfFictionalPortrayal, Western television series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfFictionalPortrayal Context triple: [Charlie Utter, genreOfFictionalPortrayal, Western television series]
-
A.
fictionalGenre
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
-
B.
genreOfAppearance
chosen
Indicates the genre or type of creative work in which an entity appears.
-
C.
genreOfCharacter
Indicates that a character belongs to or is associated with a particular genre (such as fantasy, horror, or comedy).
-
D.
portraysFictionalized
Indicates that one entity represents or depicts another entity in a fictionalized or altered manner, rather than as a strictly accurate portrayal.
-
E.
portraysCharacterInGenre
Indicates that an entity depicts or plays a character within works belonging to a specified genre.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec26311c8819093a81ff0fa43b33b |
completed | April 14, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69de657e174481909da0437556334a04 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:29 a.m.