Triple
T13667611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hearts and Bones |
E327661
|
entity |
| Predicate | hasMainCharacterGroupType |
P24067
|
FINISHED |
| Object | friends |
—
|
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: friends | Statement: [Hearts and Bones, hasMainCharacterGroupType, friends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainCharacterGroupType Context triple: [Hearts and Bones, hasMainCharacterGroupType, friends]
-
A.
hasProtagonistGroup
chosen
Indicates that a narrative work features a central group of characters who collectively serve as the main protagonists.
-
B.
hasPrimaryCharacter
Indicates that an entity features another entity as its main or central character.
-
C.
hasMainThemeCharacter
Indicates that a work (such as a story, film, or game) features a specific character as its central or primary thematic focus.
-
D.
hasMainTitleCharacter
Indicates that a work’s primary or main title is centered on, derived from, or explicitly names a particular character.
-
E.
hasTypicalCharacterType
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65832688190aea688fee0a7cbdb |
completed | April 12, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:52 p.m.