Triple
T18149380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jill Tavelman |
E434465
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Lily Collins |
—
|
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: Lily Collins | Statement: [Jill Tavelman, child, Lily Collins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lily Collins Context triple: [Jill Tavelman, child, Lily Collins]
-
A.
Lily Collins
chosen
Lily Collins is a British-American actress and model known for roles in films like "Mirror Mirror" and the series "Emily in Paris."
-
B.
Sophia Di Martino
Sophia Di Martino is a British actress best known for her role as Sylvie in the Marvel series "Loki" and for appearances in films and television including the romantic comedy "Yesterday."
-
C.
Tamsin Egerton
Tamsin Egerton is an English actress and model known for roles in films such as "St Trinian's," "Keeping Mum," and "The Look of Love."
-
D.
Lily Houghton
Lily Houghton is a fictional, adventurous British botanist and explorer from the film "Jungle Cruise."
-
E.
Lily James
Lily James is an English actress known for her roles in films such as Cinderella, Baby Driver, and Mamma Mia! Here We Go Again, as well as the TV series Downton Abbey.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de372e8081908b52fe33c870716e |
completed | April 19, 2026, 1:52 p.m. |
Created at: April 10, 2026, 10:29 a.m.