Triple
T4687687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castle Rock |
E103959
|
entity |
| Predicate | notableCharacterOrigin |
P34184
|
FINISHED |
| Object | characters and locations from Stephen King stories |
—
|
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: characters and locations from Stephen King stories | Statement: [Castle Rock, notableCharacterOrigin, characters and locations from Stephen King stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCharacterOrigin Context triple: [Castle Rock, notableCharacterOrigin, characters and locations from Stephen King stories]
-
A.
notableCharacterCreated
Indicates that one entity is a notable or significant character that was created by another entity.
-
B.
notableCharacterType
Indicates that an entity is a notable or prominent example of a specified character type or role.
-
C.
characterOrigin
chosen
Indicates the source, background, or initial context from which a character originates.
-
D.
notableArmy
Indicates that an entity is associated with an army that is historically or culturally significant or widely recognized.
-
E.
protagonistOrigin
Indicates that one entity is the origin, source, or starting point of the protagonist in a narrative or story.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd66059bfc8190885d26d05dd38df1 |
completed | March 20, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69bd6219da948190bbbb50f08573ab4d |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.