Triple
T27938985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Debbie (Knocked Up) |
E700688
|
entity |
| Predicate | hasOnScreenDaughtersPlayedBy |
P173231
|
FINISHED |
| Object | Maude Apatow |
—
|
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: Maude Apatow | Statement: [Debbie (Knocked Up), hasOnScreenDaughtersPlayedBy, Maude Apatow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnScreenDaughtersPlayedBy Context triple: [Debbie (Knocked Up), hasOnScreenDaughtersPlayedBy, Maude Apatow]
-
A.
arePlayedBy
Indicates that one or more performers (such as actors or musicians) carry out, interpret, or execute the referenced roles, characters, or pieces.
-
B.
oftenPlayedBy
Indicates that one entity frequently performs, portrays, or executes another entity, such as a role, character, or piece of music.
-
C.
hasYoungPortrayalOf
Indicates that one entity is a portrayal or depiction of another entity specifically in their younger age or earlier life stage.
-
D.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
-
E.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
- F. None of above. chosen
Provenance (4 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_69ef6a5028108190a14696d9821dde49 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6b342499c8190b85009a3f0f179e4 |
completed | May 3, 2026, 2:30 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b2a31e008190aacef03c2ebe5787 |
completed | May 3, 2026, 2:27 a.m. |
Created at: April 27, 2026, 7:16 p.m.