Triple
T1480748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sasazuka |
E30948
|
entity |
| Predicate | nearTo |
P350
|
FINISHED |
| Object |
Daitabashi
Daitabashi is a neighborhood and train station area in Tokyo, Japan, known for its residential character and access via the Keio Line.
|
E302369
|
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: Daitabashi | Statement: [Sasazuka, nearTo, Daitabashi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daitabashi Context triple: [Sasazuka, nearTo, Daitabashi]
-
A.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
B.
Kubashima
Kubashima is one of the small, uninhabited islets that make up the disputed Senkaku Islands in the East China Sea.
-
C.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
D.
Sendagaya
Sendagaya is a neighborhood in Tokyo known for its sports facilities, including the National Stadium, and its proximity to Shinjuku and Harajuku.
-
E.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
- 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: Daitabashi Triple: [Sasazuka, nearTo, Daitabashi]
Generated description
Daitabashi is a neighborhood and train station area in Tokyo, Japan, known for its residential character and access via the Keio Line.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daitabashi Target entity description: Daitabashi is a neighborhood and train station area in Tokyo, Japan, known for its residential character and access via the Keio Line.
-
A.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
B.
Kubashima
Kubashima is one of the small, uninhabited islets that make up the disputed Senkaku Islands in the East China Sea.
-
C.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
D.
Sendagaya
Sendagaya is a neighborhood in Tokyo known for its sports facilities, including the National Stadium, and its proximity to Shinjuku and Harajuku.
-
E.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c67699848190852e376efe22737c |
completed | March 1, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afce6ea6f88190b455439f73a02728 |
completed | March 10, 2026, 7:55 a.m. |
| NEDg | Description generation | batch_69afd27a5cc88190989f93505c1e4cd3 |
completed | March 10, 2026, 8:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afd2d6be848190a5444fc8341cf4b1 |
completed | March 10, 2026, 8:14 a.m. |
Created at: March 1, 2026, 8:11 p.m.