Triple
T3031297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Boyega |
E82900
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Boyega |
E82900
|
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: Boyega | Statement: [John Boyega, hasSurname, Boyega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boyega Context triple: [John Boyega, hasSurname, Boyega]
-
A.
Boyega
chosen
Boyega is the surname of British actor and producer John Boyega, best known for his role as Finn in the Star Wars sequel trilogy.
-
B.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
C.
Malyk
Malyk is a given name, typically a variant spelling of Malik, used as a masculine personal name in various cultures.
-
D.
Lyova
Lyova is a Russian diminutive form of the male given name Lev.
-
E.
Bekwarra
Bekwarra is a notable town and local government area in southeastern Nigeria, recognized for its predominantly agrarian community and cultural heritage within Cross River State.
- 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_69ad8b21a62881908ec5dd4fba4a187c |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9aee2fec81908116939a8d773fc4 |
completed | March 8, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1debd245c819081eb2dec470f9156 |
completed | March 11, 2026, 9:29 p.m. |
Created at: March 8, 2026, 3:01 p.m.