Triple
T15620281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shohei |
E375532
|
entity |
| Predicate | nameElement |
P27866
|
FINISHED |
| Object | Sho |
E1089400
|
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: Sho | Statement: [Shohei, nameElement, Sho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sho Context triple: [Shohei, nameElement, Sho]
-
A.
Sho
chosen
Sho is a given name commonly used in Japan, often for males, and can be written with various kanji characters that convey different meanings.
-
B.
Shou
Shou is the personal name of King Zhou of Shang, the last ruler of China’s Shang dynasty, often depicted in tradition as a tyrannical and decadent monarch.
-
C.
Shon
Shon is a given name that functions as an alternative spelling of the more common name Shaun (or Sean).
-
D.
Shoki
"Shoki" is a popular Nigerian street-hop song by Lil Kesh that helped propel him to mainstream fame and popularized a viral dance of the same name.
-
E.
Shin
Shin is a common Japanese given name element that often conveys meanings like “truth,” “new,” or “heart,” depending on the kanji used.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e997ce481909b2f10d25705fbc6 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f3b643c819093230df6cfe440b9 |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:13 a.m.