Triple
T4214751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsukuba |
E94187
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Tsukuba Capio
Tsukuba Capio is a cultural and performing arts center in Tsukuba, Japan, known for hosting theater, music, and community events.
|
E422021
|
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: Tsukuba Capio | Statement: [Tsukuba, hasLandmark, Tsukuba Capio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsukuba Capio Context triple: [Tsukuba, hasLandmark, Tsukuba Capio]
-
A.
Kansai Kūkō
Kansai Kūkō is a major international airport built on an artificial island in Osaka Bay, serving the Kansai region of Japan.
-
B.
Todai
Todai is the common nickname for the University of Tokyo, Japan’s most prestigious and influential national research university.
-
C.
Meijō
Meijō is the Japanese name for Nagoya Castle, a historic and iconic samurai-era fortress in Nagoya, Japan.
-
D.
Gaimushō
Gaimushō is Japan’s Ministry of Foreign Affairs, responsible for managing the country’s diplomatic relations and international policies.
-
E.
Tsukuba Science City
Tsukuba Science City is a planned research and academic hub in Ibaraki Prefecture, Japan, known for its concentration of universities, national laboratories, and high-tech industries.
- 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: Tsukuba Capio Triple: [Tsukuba, hasLandmark, Tsukuba Capio]
Generated description
Tsukuba Capio is a cultural and performing arts center in Tsukuba, Japan, known for hosting theater, music, and community events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tsukuba Capio Target entity description: Tsukuba Capio is a cultural and performing arts center in Tsukuba, Japan, known for hosting theater, music, and community events.
-
A.
Kansai Kūkō
Kansai Kūkō is a major international airport built on an artificial island in Osaka Bay, serving the Kansai region of Japan.
-
B.
Todai
Todai is the common nickname for the University of Tokyo, Japan’s most prestigious and influential national research university.
-
C.
Meijō
Meijō is the Japanese name for Nagoya Castle, a historic and iconic samurai-era fortress in Nagoya, Japan.
-
D.
Gaimushō
Gaimushō is Japan’s Ministry of Foreign Affairs, responsible for managing the country’s diplomatic relations and international policies.
-
E.
Tsukuba Science City
Tsukuba Science City is a planned research and academic hub in Ibaraki Prefecture, Japan, known for its concentration of universities, national laboratories, and high-tech industries.
- 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34be8ba408190baee362e5abbe75b |
completed | March 12, 2026, 11:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5963779d08190a95eb110361bf1f1 |
completed | March 14, 2026, 5:09 p.m. |
| NEDg | Description generation | batch_69b597f5ec8481909408b6b49994bbe8 |
completed | March 14, 2026, 5:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5985c8f6081909c479e89bc1ca449 |
completed | March 14, 2026, 5:18 p.m. |
Created at: March 12, 2026, 11:04 p.m.