Triple
T4716608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Boyega |
E104655
|
entity |
| Predicate | familyName |
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, familyName, Boyega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boyega Context triple: [John Boyega, familyName, 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.
Boorga
Boorga is a small rural locality within the Hay Shire local government area in New South Wales, Australia.
-
C.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
D.
Boebe
Boebe was an ancient town in the region of Magnesia in Thessaly, Greece, known from classical sources and associated with nearby Lake Boebeis.
-
E.
Jebe
Jebe was one of Genghis Khan’s most brilliant generals, renowned for his daring cavalry campaigns and key role in the early Mongol conquests across Central Asia and into Eastern Europe.
- 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_69bd43ec4a348190bc41afae43375e71 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd640a32ec8190850146957885c3cf |
completed | March 20, 2026, 3:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be1088103c819098296ce700697e90 |
completed | March 21, 2026, 3:29 a.m. |
Created at: March 20, 2026, 1:18 p.m.