Triple
T10322644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Hudson |
E242672
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Deepwater Horizon |
E161217
|
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: Deepwater Horizon | Statement: [Kate Hudson, notableWork, Deepwater Horizon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deepwater Horizon Context triple: [Kate Hudson, notableWork, Deepwater Horizon]
-
A.
Deepwater Horizon
chosen
Deepwater Horizon is a 2016 disaster drama film that depicts the real-life 2010 offshore drilling rig explosion and oil spill in the Gulf of Mexico.
-
B.
Calypso Deep
Calypso Deep is the deepest known point in the Mediterranean Sea, located in the Hellenic Trench near Greece.
-
C.
Ocean Deep
Ocean Deep is an episode of the documentary series "Planet Earth" that explores the mysterious and extreme environments of the world's deepest oceans and the unique life forms that inhabit them.
-
D.
Deep Sea
Deep Sea is an aquarium exhibit showcasing the mysterious life forms and extreme environments found in the ocean’s deepest regions.
-
E.
Blue Waters
Blue Waters is a petascale supercomputer system designed for large-scale scientific and engineering research, formerly operated at the National Center for Supercomputing Applications at the University of Illinois.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d6cdb6cc8190b37ca4494287128b |
completed | April 7, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71da2053481908fe5ed097b480cdd |
completed | April 9, 2026, 3:31 a.m. |
Created at: April 6, 2026, 11:50 a.m.