Triple
T14016199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Girl |
E337209
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Griffin Dunne |
E387968
|
NE 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: Griffin Dunne | Statement: [My Girl, castMember, Griffin Dunne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Griffin Dunne Context triple: [My Girl, castMember, Griffin Dunne]
-
A.
Griffin Dunne
chosen
Griffin Dunne is an American actor, director, and producer known for roles in films like "An American Werewolf in London" and "After Hours."
-
B.
Andrew Dorff
Andrew Dorff was an American country music songwriter known for penning hits for artists such as Blake Shelton, Kenny Chesney, and Rascal Flatts.
-
C.
Gil Pender
Gil Pender is the nostalgic, time-traveling screenwriter protagonist of Woody Allen’s film "Midnight in Paris," portrayed by Owen Wilson.
-
D.
William Devane
William Devane is an American actor known for his intense, often authoritative roles in film and television, including prominent performances in projects like "Knots Landing" and "24."
-
E.
Jon Cryer
Jon Cryer is an American actor best known for his role as Alan Harper on the sitcom "Two and a Half Men" and for his work in films like "Pretty in Pink."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2f396b648190927e5718c3bb6511 |
completed | April 14, 2026, 12:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbacac12608190a5e3d970ec3cda45 |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:19 p.m.