Triple
T18547215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Parish Bartlett |
E453267
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Apple |
—
|
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: Apple | Statement: [Apple Parish Bartlett, givenName, Apple]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apple Context triple: [Apple Parish Bartlett, givenName, Apple]
-
A.
Apple
Apple is a widely cultivated fruit known for its crisp texture, sweet-tart flavor, and central role in cuisines and agricultural traditions around the world.
-
B.
Apple
"Apple" is the only studio album by the American rock band Mother Love Bone, recognized as a seminal release in the early Seattle grunge scene.
-
C.
Apple
chosen
Apple is a common English given name, most famously borne by Apple Martin, the daughter of Gwyneth Paltrow and Chris Martin.
-
D.
Apple
Apple is a renowned record label and multimedia company founded by The Beatles, best known for releasing and managing their music and related projects.
-
E.
Apple Inc.
Apple Inc. is a multinational technology company best known for designing and selling consumer electronics like the iPhone, Mac, and iPad, along with software and digital services.
- 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_69d8d388b0c881908e610a1c45b52640 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e534bd0614819083e326d5f22c19ac |
completed | April 19, 2026, 8:02 p.m. |
Created at: April 10, 2026, 11:38 a.m.