Triple
T26115622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camp Green Lake |
E658814
|
entity |
| Predicate | hasInmateFictionalCharacter |
P48975
|
FINISHED |
| Object | Stanley Yelnats IV |
—
|
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: Stanley Yelnats IV | Statement: [Camp Green Lake, hasInmateFictionalCharacter, Stanley Yelnats IV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInmateFictionalCharacter Context triple: [Camp Green Lake, hasInmateFictionalCharacter, Stanley Yelnats IV]
-
A.
fictionalPrisoner
chosen
Indicates that an entity is portrayed as a prisoner within a fictional or narrative context.
-
B.
hasFictionalStaffMember
Indicates that an entity includes or employs a staff member who is a fictional character.
-
C.
isFictionalCharacter
Indicates that the subject is a character that exists only in fiction rather than in real life.
-
D.
isFictionalPersonFrom
Indicates that a fictional person originates from or is associated with a particular place or source.
-
E.
hasFictionalAddressee
Indicates that an entity (such as a text or communication) is directed toward or addressed to an addressee that is fictional rather than a real person or audience.
- 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_69ee5bc20298819099a42be042eb2349 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
Created at: April 26, 2026, 8:05 p.m.