Triple
T14488304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Who's Laughing Now |
E359293
|
entity |
| Predicate | featuresChildActressAsYoungJessieJ |
P97663
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Who's Laughing Now, featuresChildActressAsYoungJessieJ, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresChildActressAsYoungJessieJ Context triple: [Who's Laughing Now, featuresChildActressAsYoungJessieJ, Yes]
-
A.
youngerVersionPortrayedBy
Indicates that one person portrays a younger version of another person, typically in a film, television show, or similar narrative work.
-
B.
childPerformer
Indicates a relationship where the subject is a performer who is a child, typically under a certain age, participating in a performance or production.
-
C.
playedByChildActor
chosen
Indicates that a role or character is portrayed by an actor who is a child at the time of performance.
-
D.
portraysYoungerVersionOfCharacterFrom
Indicates that one character is depicted as a younger version of another character from a specified source.
-
E.
characterPlayedByKathleenQuinlan
Indicates that a given character is portrayed or acted by Kathleen Quinlan.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de930bd1d48190abd6c47da0a3ebc8 |
completed | April 14, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.