Triple
T6760073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamigyo-ku, Kyoto |
E154567
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object |
上京区
上京区 is a central ward of Kyoto, Japan, known for its historic temples, traditional townscapes, and cultural landmarks including parts of the Kyoto Imperial Palace area.
|
E618716
|
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: 上京区 | Statement: [Kamigyo-ku, Kyoto, nativeName, 上京区]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 上京区 Context triple: [Kamigyo-ku, Kyoto, nativeName, 上京区]
-
A.
Fuxing District
Fuxing District is an urban administrative district of Handan City in Hebei Province, China.
-
B.
Yingquan District
Yingquan District is an urban administrative district of the city of Fuyang in Anhui Province, China.
-
C.
Yonghe District
Yonghe District is a densely populated urban district in northern Taiwan known for its residential neighborhoods and proximity to central Taipei.
-
D.
Sanzhi District
Sanzhi District is a rural coastal district in northern Taiwan known for its scenic landscapes, hot springs, and agricultural produce within New Taipei City.
-
E.
Tieshan District
Tieshan District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China, known for its industrial and mining activities.
- 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: 上京区 Triple: [Kamigyo-ku, Kyoto, nativeName, 上京区]
Generated description
上京区 is a central ward of Kyoto, Japan, known for its historic temples, traditional townscapes, and cultural landmarks including parts of the Kyoto Imperial Palace area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 上京区 Target entity description: 上京区 is a central ward of Kyoto, Japan, known for its historic temples, traditional townscapes, and cultural landmarks including parts of the Kyoto Imperial Palace area.
-
A.
Fuxing District
Fuxing District is an urban administrative district of Handan City in Hebei Province, China.
-
B.
Yingquan District
Yingquan District is an urban administrative district of the city of Fuyang in Anhui Province, China.
-
C.
Yonghe District
Yonghe District is a densely populated urban district in northern Taiwan known for its residential neighborhoods and proximity to central Taipei.
-
D.
Sanzhi District
Sanzhi District is a rural coastal district in northern Taiwan known for its scenic landscapes, hot springs, and agricultural produce within New Taipei City.
-
E.
Tieshan District
Tieshan District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China, known for its industrial and mining activities.
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d21143748190beaab2488971d65b |
completed | March 27, 2026, 6:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c712b0926c81909601f21407526fd9 |
completed | March 27, 2026, 11:28 p.m. |
| NEDg | Description generation | batch_69c7135106288190b5b20523c3efa229 |
completed | March 27, 2026, 11:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7141cd52c8190a783590ad1067840 |
completed | March 27, 2026, 11:34 p.m. |
Created at: March 27, 2026, 2:12 p.m.