Triple
T16048520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andy Hopper |
E389287
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hopper |
E183417
|
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: Hopper | Statement: [Andy Hopper, familyName, Hopper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hopper Context triple: [Andy Hopper, familyName, Hopper]
-
A.
Hopper
chosen
Hopper is a surname most famously associated with Edward Hopper, the American realist painter known for his evocative depictions of modern urban life and isolation.
-
B.
Hopper
Hopper is an NVIDIA GPU architecture designed for high-performance computing and AI workloads, featuring advanced capabilities such as enhanced Tensor Core acceleration.
-
C.
Hopper
Hopper is the ruthless grasshopper leader and main villain in Pixar's animated film "A Bug's Life," known for terrorizing an ant colony to maintain his power.
-
D.
Hopper
Hopper is a supporting character in the 2015 romantic comedy film "Mr. Right," involved in the movie’s offbeat, action-driven storyline.
-
E.
Hopper Penn
Hopper Penn is an American actor and model, best known as the son of actors Sean Penn and Robin Wright and for his roles in independent films.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e18360464881909fd4d3bcb4ffb7f5 |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbddc25481908fca660c4f14eaff |
completed | May 10, 2026, 1:14 a.m. |
Created at: April 10, 2026, 4:56 a.m.