Triple
T4971838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jun John Sakurai |
E111670
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jun |
E375764
|
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: Jun | Statement: [Jun John Sakurai, givenName, Jun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jun Context triple: [Jun John Sakurai, givenName, Jun]
-
A.
Jun
chosen
Jun is a common Japanese given name that can be used for people of any gender and carries various meanings depending on the kanji characters used.
-
B.
Juin
Juin is the surname of Alphonse Juin, a prominent French general and Marshal of France during World War II.
-
C.
June
June is an early-summer month in the Northern Hemisphere often associated with favorable weather for outdoor activities and mountaineering.
-
D.
July
July is the seventh month of the year, typically associated with mid-summer in the Northern Hemisphere and named after Julius Caesar.
-
E.
May
May is a common English surname borne by numerous individuals, including former UK Prime Minister Theresa May.
- 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7214e18c81909db1c838a4cce78d |
completed | March 20, 2026, 4:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81fa9108819089a6258e3a88f0cb |
completed | March 21, 2026, 11:33 a.m. |
Created at: March 20, 2026, 1:33 p.m.