Triple
T16986302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danielle Panabaker |
E412073
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | Summerland |
E1173496
|
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: Summerland | Statement: [Danielle Panabaker, appearedIn, Summerland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Summerland Context triple: [Danielle Panabaker, appearedIn, Summerland]
-
A.
Summerland
Summerland is a small unincorporated coastal community in Santa Barbara County, California, known for its beaches, ocean views, and relaxed residential character.
-
B.
Summerland
Summerland is a small town in British Columbia’s Okanagan Valley known for its orchards, wineries, and scenic lakeside setting.
-
C.
Summerland
"Summerland" is a fantasy novel by Michael Chabon that blends baseball, American folklore, and a coming-of-age quest across parallel worlds.
-
D.
Summerland
chosen
"Summerland" is a 2020 British drama film set during World War II, following a reclusive writer whose life changes when she is forced to care for an evacuated young boy.
-
E.
Summerland Hotel
Summerland Hotel was a prominent hotel that became notable for its role in the historic Battle of the Hotels.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d27b58908190a643bcbd105b1849 |
completed | April 18, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc1109a081908890bbd5958c76c2 |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 10, 2026, 5:32 a.m.