Triple
T10236484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weeds |
E243476
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Lane Smith |
E248328
|
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: Lane Smith | Statement: [Weeds, starring, Lane Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lane Smith Context triple: [Weeds, starring, Lane Smith]
-
A.
Lane Smith
chosen
Lane Smith was an American character actor known for his roles in film and television, including portrayals of authoritative and often gruff figures.
-
B.
Oliver Jeffers
Oliver Jeffers is a Northern Irish artist, illustrator, and author best known for his distinctive picture books and visual storytelling.
-
C.
Debbie Ridpath Ohi
Debbie Ridpath Ohi is a Canadian author and illustrator best known for her whimsical, expressive artwork in children's picture books and middle-grade fiction.
-
D.
Amy Krouse Rosenthal
Amy Krouse Rosenthal was an American author, filmmaker, and radio host best known for her inventive children's books and poignant personal essays, including her widely read New York Times piece "You May Want to Marry My Husband."
-
E.
Lauren Munsch
Lauren Munsch is a film producer best known for her work on the coming-of-age drama "The Wackness."
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d219ab04819094a17c96bf1d65ae |
completed | April 7, 2026, 9:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f762732481909246dcb768074643 |
completed | April 9, 2026, 12:48 a.m. |
Created at: April 6, 2026, 11:22 a.m.