Triple
T15712044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The One I Love |
E380861
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Jennifer Lilly |
E1180143
|
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: Jennifer Lilly | Statement: [The One I Love, editedBy, Jennifer Lilly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jennifer Lilly Context triple: [The One I Love, editedBy, Jennifer Lilly]
-
A.
Jennifer Lilly
chosen
Jennifer Lilly is a film editor known for her work on the feature film "Robot & Frank."
-
B.
Lilly Burns
Lilly Burns is an American television producer and co-founder of the production company Jax Media, known for her work on various acclaimed TV series.
-
C.
Lili Simmons
Lili Simmons is an American actress and model known for her roles in television series such as Banshee, True Detective, and The Purge.
-
D.
Lisa Lynne
Lisa Lynne is an American Celtic harpist and composer known for her melodic, folk-inspired instrumental music and collaborations in the new age and world music genres.
-
E.
Lila Garrett
Lila Garrett was an American television producer, screenwriter, and political activist known for her work on socially conscious TV projects and her outspoken progressive views.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f8f5d6081908243fa59b46b7c76 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa9341a0c81909057dc338f218b85 |
completed | May 9, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:45 a.m.