Triple
T3877493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eisaku Inoue |
E92537
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Inoue
Inoue is a common Japanese surname borne by numerous notable figures across fields such as politics, sports, literature, and the arts.
|
E497312
|
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: Inoue | Statement: [Eisaku Inoue, familyName, Inoue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inoue Context triple: [Eisaku Inoue, familyName, Inoue]
-
A.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
-
B.
Ichikawa
Ichikawa is a city in Chiba Prefecture, Japan, located just east of Tokyo and known as a residential and commercial hub within the Greater Tokyo Area.
-
C.
Murayama
Murayama is a Japanese surname borne by various notable individuals across fields such as politics, science, and the arts.
-
D.
Nishiwaki
Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
-
E.
Tanaka
Tanaka is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and other fields.
- 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: Inoue Triple: [Eisaku Inoue, familyName, Inoue]
Generated description
Inoue is a common Japanese surname borne by numerous notable figures across fields such as politics, sports, literature, and the arts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Inoue Target entity description: Inoue is a common Japanese surname borne by numerous notable figures across fields such as politics, sports, literature, and the arts.
-
A.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
-
B.
Ichikawa
Ichikawa is a city in Chiba Prefecture, Japan, located just east of Tokyo and known as a residential and commercial hub within the Greater Tokyo Area.
-
C.
Murayama
Murayama is a Japanese surname borne by various notable individuals across fields such as politics, science, and the arts.
-
D.
Nishiwaki
Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
-
E.
Tanaka
Tanaka is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and other fields.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec72fa7c81909c73b3cf90597e9a |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69becf8f926481908f6e1cf33fc79a04 |
completed | March 21, 2026, 5:04 p.m. |
| NEDg | Description generation | batch_69bed09cf66481909f7aa65de3fce54d |
completed | March 21, 2026, 5:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bed136a790819083ec5b8ae923fa3e |
completed | March 21, 2026, 5:11 p.m. |
Created at: March 9, 2026, 3:20 p.m.