Triple
T17143336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rina Satō |
E416024
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Rina |
E329046
|
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: Rina | Statement: [Rina Satō, givenName, Rina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rina Context triple: [Rina Satō, givenName, Rina]
-
A.
Rina
chosen
Rina is a feminine given name commonly used as a short or diminutive form of longer names such as Caterina.
-
B.
Riza
Riza is a masculine given name commonly used in various cultures, often with roots in Arabic and Turkish languages.
-
C.
Geisa
Geisa is a small historic town in the state of Thuringia in central Germany, near the former inner-German border.
-
D.
Rika
Rika is a feminine given name, often used as a short or diminutive form of longer names such as Henrike, Frederika, or Erika.
-
E.
Sanae
Sanae is a Japanese feminine given name borne by various notable figures in politics, entertainment, and other fields.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f2d73c3c81908b875023bb925edb |
completed | April 18, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01415718c88190834fedae7b01ac69 |
completed | May 11, 2026, 2:39 a.m. |
Created at: April 10, 2026, 5:36 a.m.