Triple
T23442627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | H. Jon Benjamin as Bob Belcher |
E565443
|
entity |
| Predicate | characterChild |
P121316
|
FINISHED |
| Object | Tina Belcher |
—
|
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: Tina Belcher | Statement: [H. Jon Benjamin as Bob Belcher, characterChild, Tina Belcher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterChild Context triple: [H. Jon Benjamin as Bob Belcher, characterChild, Tina Belcher]
-
A.
childCharacter
Indicates that one entity is a child version or child role of another character entity.
-
B.
childOfCharacter
chosen
Indicates that one character is the offspring (biological, adopted, or otherwise recognized child) of another character.
-
C.
childIn
Indicates that one entity is the offspring or direct descendant of another entity.
-
D.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
E.
character3
Indicates a tertiary or additional character role associated with an entity, typically the third distinct character linked within a given context or work.
- 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_69e24584f9488190bb32730bd2ce023e |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a64654e88190b530958b27b32412 |
completed | April 29, 2026, 6:33 a.m. |
| PD | Predicate disambiguation | batch_69f061f92da081908e7f1d0cd1e9b01c |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 5:51 p.m.