Triple
T6785722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yotsuya |
E155796
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object |
Ichigaya
Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
|
E688152
|
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: Ichigaya | Statement: [Yotsuya, adjacentTo, Ichigaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ichigaya Context triple: [Yotsuya, adjacentTo, Ichigaya]
-
A.
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.
-
B.
Takarano
Takarano is a small settlement on the atoll of Tabiteuea in the island nation of Kiribati, located in the central Pacific Ocean.
-
C.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
-
D.
Seishirō
Seishirō is a Japanese given name commonly used for male individuals.
-
E.
Oyamazaki
Oyamazaki is a town in Kyoto Prefecture, Japan, known for its historical significance and scenic location at the confluence of major rivers and transportation routes.
- 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: Ichigaya Triple: [Yotsuya, adjacentTo, Ichigaya]
Generated description
Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ichigaya Target entity description: Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
-
A.
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.
-
B.
Takarano
Takarano is a small settlement on the atoll of Tabiteuea in the island nation of Kiribati, located in the central Pacific Ocean.
-
C.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
-
D.
Seishirō
Seishirō is a Japanese given name commonly used for male individuals.
-
E.
Oyamazaki
Oyamazaki is a town in Kyoto Prefecture, Japan, known for its historical significance and scenic location at the confluence of major rivers and transportation routes.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d28de0348190998751fd546bfd02 |
completed | March 27, 2026, 6:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8d67da5708190973ac88aa67e32b1 |
completed | March 29, 2026, 7:36 a.m. |
| NEDg | Description generation | batch_69c8d6e89c5081908638fdfa24abf4dc |
completed | March 29, 2026, 7:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8d740c4848190b34f4cf7ad708592 |
completed | March 29, 2026, 7:39 a.m. |
Created at: March 27, 2026, 2:14 p.m.