Triple
T13891463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Belushi |
E333980
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Belushi |
E331348
|
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: Belushi | Statement: [John Belushi, familyName, Belushi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belushi Context triple: [John Belushi, familyName, Belushi]
-
A.
Belushi
chosen
Belushi is a surname most famously associated with American comedians and actors John and Jim Belushi.
-
B.
Barkhad
Barkhad is a male given name notably borne by Somali-American actor Barkhad Abdi.
-
C.
Benne
Benne is a type of bean, often associated with heirloom or regional varieties used in traditional cooking.
-
D.
Jobu
Jobu is the fictional voodoo deity that baseball player Pedro Cerrano prays to for help with his hitting in the film "Major League."
-
E.
Taron
Taron is a masculine given name most prominently associated with Welsh actor Taron Egerton.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a537d4819093c2bae2a244816a |
completed | April 14, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c71a43908190bc7537f0a2379599 |
completed | May 3, 2026, 10:07 p.m. |
Created at: April 9, 2026, 10:15 p.m.