Triple
T29798660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johnny Wadd in Denmark |
E756625
|
entity |
| Predicate | seriesCharacterType |
P60013
|
FINISHED |
| Object | hardboiled detective |
—
|
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: hardboiled detective | Statement: [Johnny Wadd in Denmark, seriesCharacterType, hardboiled detective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesCharacterType Context triple: [Johnny Wadd in Denmark, seriesCharacterType, hardboiled detective]
-
A.
typeOfCharacter
chosen
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
B.
relatedCharacterType
Indicates that one character has a specified type of relationship or role in connection to another character.
-
C.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
D.
storyCharacterizedAs
Indicates that a story is described, portrayed, or defined as having a particular quality, style, or attribute.
-
E.
relatedSeriesCharacter
Indicates that one character is connected to another by appearing in a related or associated series within the same broader narrative universe.
- 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_69f22454583081908927516cb9938d1d |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: April 29, 2026, 5:17 p.m.