Triple
T28518039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seth Green as young Richie Tozier |
E721677
|
entity |
| Predicate | hasAdultCounterpartCharacter |
P135468
|
FINISHED |
| Object | adult Richie Tozier |
—
|
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: adult Richie Tozier | Statement: [Seth Green as young Richie Tozier, hasAdultCounterpartCharacter, adult Richie Tozier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdultCounterpartCharacter Context triple: [Seth Green as young Richie Tozier, hasAdultCounterpartCharacter, adult Richie Tozier]
-
A.
hasAdultNarratorVersionOfCharacter
chosen
Indicates that one character represents the adult narrator version of another character.
-
B.
isAdultCharacter
Indicates that a character has reached adulthood, typically meeting the age or maturity criteria defining an adult within the given context.
-
C.
portrayedAsAdultBy
Indicates that one entity is depicted or represented as an adult by another entity (such as an artist, author, or creator).
-
D.
appearsAsAdultIn
Indicates that an entity is depicted or presented in its adult form within a specified context, such as a work, scene, or time period.
-
E.
hasHumanPartnerCharacter
Indicates that an entity is associated with a partner character who is human.
- 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_69f01a5cbcc4819083fb4e723378713e |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 28, 2026, 3:18 a.m.