Triple
T8196332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stan Mikita |
E191438
|
entity |
| Predicate | laterFamilyName |
P18
|
FINISHED |
| Object | Mikita |
E718467
|
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: Mikita | Statement: [Stan Mikita, laterFamilyName, Mikita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mikita Context triple: [Stan Mikita, laterFamilyName, Mikita]
-
A.
Mikita
chosen
Mikita is a given name and surname of Slavic origin used by various notable individuals.
-
B.
Miya
Miya is a Japanese honorific suffix historically used in imperial and aristocratic titles, particularly within branches of the Japanese Imperial Family such as the Higashikuni-no-miya.
-
C.
Miya
Miya is a Chadic language spoken in parts of northern Nigeria, known for its complex tonal system and Afroasiatic linguistic roots.
-
D.
Makiko
Makiko is a Japanese feminine given name commonly borne by women in Japan and of Japanese heritage.
-
E.
Shizu
Shizu is the posthumous temple name by which Emperor Guangwu, the restorer and founding ruler of the Eastern Han dynasty in China, is venerated in ancestral rites.
- 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_69ca82c6e9548190a4c5ca14516e4417 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5c222e7081908aebce9253cfe515 |
completed | March 31, 2026, 5:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd34a11138819093b9a17ab8b8ec8a |
completed | April 1, 2026, 3:07 p.m. |
Created at: March 30, 2026, 5:42 p.m.