Triple
T37576316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asian Jim |
E934829
|
entity |
| Predicate | hasChildInPrank |
P185980
|
FINISHED |
| Object | Cecelia Halpert |
—
|
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: Cecelia Halpert | Statement: [Asian Jim, hasChildInPrank, Cecelia Halpert]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChildInPrank Context triple: [Asian Jim, hasChildInPrank, Cecelia Halpert]
-
A.
isChildIn
Indicates that one entity is the child (offspring or subordinate in a family or hierarchical structure) of another entity.
-
B.
hasChildIn
Indicates that one entity has a child who is located in, associated with, or present within another specified entity or context.
-
C.
hasOnScreenSonWith
chosen
Indicates that two entities are related such that one appears as the on-screen son of the other in a visual media context.
-
D.
hasChildInCoverIdentity
Indicates that an entity has a child who is associated with or exists under the entity’s cover or assumed identity, rather than their true identity.
-
E.
hasChildProtagonist
Indicates that the work features a child as its main or central character.
- 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_69f76ecd99148190be327e391a70f5b6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff2fbae9b48190847eefa1c227d43e |
completed | May 9, 2026, 12:59 p.m. |
| PD | Predicate disambiguation | batch_69ff2f2218048190a32224a648182b5d |
completed | May 9, 2026, 12:57 p.m. |
Created at: May 3, 2026, 4:17 p.m.