Triple
T16056500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tusk |
E389493
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Jennifer Schwalbach Smith |
—
|
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: Jennifer Schwalbach Smith | Statement: [Tusk, hasCastMember, Jennifer Schwalbach Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jennifer Schwalbach Smith Context triple: [Tusk, hasCastMember, Jennifer Schwalbach Smith]
-
A.
Jennifer Schwalbach Smith
chosen
Jennifer Schwalbach Smith is an American actress, podcaster, and former reporter best known for her frequent collaborations with her husband, filmmaker Kevin Smith, in his View Askewniverse films.
-
B.
Amy Smith
Amy Smith is the daughter of John Smith.
-
C.
Jennifer Smith
Jennifer Smith is a Bermudian politician who served as Premier and was the first woman to lead the government of Bermuda.
-
D.
Jennifer Smith
Jennifer Smith is the daughter of John Smith.
-
E.
Emily Friehl
Emily Friehl is a free-spirited, aspiring actress and photographer who forms a years-long, will-they-won’t-they romantic connection with Oliver in the film "A Lot Like Love."
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837579488190964ca004c2eb01c4 |
completed | April 17, 2026, 12:48 a.m. |
Created at: April 10, 2026, 4:56 a.m.