Triple
T26089361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stool Pigeon |
E658072
|
entity |
| Predicate | relatedCharacterInWork |
P37304
|
FINISHED |
| Object | King Hedley II |
—
|
NE NERFINISHED |
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: King Hedley II | Statement: [Stool Pigeon, relatedCharacterInWork, King Hedley II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedCharacterInWork Context triple: [Stool Pigeon, relatedCharacterInWork, King Hedley II]
-
A.
relatedCharacter
chosen
Indicates that one character has a specified relationship or association with another character.
-
B.
relatedCharacterContext
Indicates a contextual relationship between characters, such as roles, interactions, or situational connections that link them within a specific narrative or setting.
-
C.
relatedCharacterType
Indicates that one character has a specified type of relationship or role in connection to another character.
-
D.
relationshipToCharacter
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
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_69ee5bbfc4d08190a1b206d0ac3a1e8d |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69fdd5fba5048190b7d430ae2054a1fd |
completed | May 8, 2026, 12:24 p.m. |
| PD | Predicate disambiguation | batch_69fdd35f76f88190a1854ea27132f9c7 |
completed | May 8, 2026, 12:13 p.m. |
Created at: April 26, 2026, 7:45 p.m.