Triple
T22050720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanaya Hanzo |
E544873
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Kanaya
Kanaya is a Japanese surname that may refer to various individuals, places, or entities in Japan.
|
E1515696
|
NE FINISHED |
How this triple was built (4 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: Kanaya | Statement: [Kanaya Hanzo, familyName, Kanaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kanaya Context triple: [Kanaya Hanzo, familyName, Kanaya]
-
A.
K’ana
K’ana is an alternative name for Espinar Province, a highland administrative region in the Cusco Department of southern Peru known for its Andean culture and mining activities.
-
B.
Kaiya
Kaiya is a feminine given name used in various cultures, often associated with meanings related to the sea, forgiveness, or purity.
-
C.
Kamia
Kamia are an Indigenous Native American people historically associated with the region around the lower Colorado River and nearby desert areas of the southwestern United States and northern Mexico.
-
D.
Yamanakako
Yamanakako is a village in Yamanashi Prefecture, Japan, known for Lake Yamanaka, one of the Fuji Five Lakes located near Mount Fuji.
-
E.
Alna Kōki
Alna Kōki is a Japanese rolling stock manufacturer known for producing electric multiple units and other railway vehicles for private railway operators.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kanaya Triple: [Kanaya Hanzo, familyName, Kanaya]
Generated description
Kanaya is a Japanese surname that may refer to various individuals, places, or entities in Japan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kanaya Target entity description: Kanaya is a Japanese surname that may refer to various individuals, places, or entities in Japan.
-
A.
K’ana
K’ana is an alternative name for Espinar Province, a highland administrative region in the Cusco Department of southern Peru known for its Andean culture and mining activities.
-
B.
Kaiya
Kaiya is a feminine given name used in various cultures, often associated with meanings related to the sea, forgiveness, or purity.
-
C.
Kamia
Kamia are an Indigenous Native American people historically associated with the region around the lower Colorado River and nearby desert areas of the southwestern United States and northern Mexico.
-
D.
Yamanakako
Yamanakako is a village in Yamanashi Prefecture, Japan, known for Lake Yamanaka, one of the Fuji Five Lakes located near Mount Fuji.
-
E.
Alna Kōki
Alna Kōki is a Japanese rolling stock manufacturer known for producing electric multiple units and other railway vehicles for private railway operators.
- F. None of above. chosen
Provenance (5 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1283386f081908b70df81f38a5b1c |
completed | April 28, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a7b79594c8190b66439167d7a3cbd |
completed | May 18, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_6a0a7cb2b0c88190930290efe1d8371a |
completed | May 18, 2026, 2:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a7e131ae48190a564a86d3d691e1a |
completed | May 18, 2026, 2:48 a.m. |
Created at: April 16, 2026, 8:26 p.m.