Triple
T886191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kindai University |
E19135
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
Kindai
Kindai is a major private university in Japan known for its comprehensive academic programs and strong research in fields such as science, engineering, and fisheries.
|
E104598
|
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: Kindai | Statement: [Kindai University, abbreviation, Kindai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kindai Context triple: [Kindai University, abbreviation, Kindai]
-
A.
Kyodai
Kyodai is the common abbreviated name for Kyoto University, one of Japan’s most prestigious national research universities.
-
B.
Todai
Todai is the common nickname for the University of Tokyo, Japan’s most prestigious and influential national research university.
-
C.
Takatsuki
Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
-
D.
Kaisei Academy
Kaisei Academy is a prestigious Japanese boys' secondary school in Tokyo known for its rigorous academics and history of producing many prominent political and intellectual leaders.
-
E.
Koreiz
Koreiz is a resort settlement on the southern coast of Crimea, known for its seaside location and historic villas.
- 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: Kindai Triple: [Kindai University, abbreviation, Kindai]
Generated description
Kindai is a major private university in Japan known for its comprehensive academic programs and strong research in fields such as science, engineering, and fisheries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kindai Target entity description: Kindai is a major private university in Japan known for its comprehensive academic programs and strong research in fields such as science, engineering, and fisheries.
-
A.
Kyodai
Kyodai is the common abbreviated name for Kyoto University, one of Japan’s most prestigious national research universities.
-
B.
Todai
Todai is the common nickname for the University of Tokyo, Japan’s most prestigious and influential national research university.
-
C.
Takatsuki
Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
-
D.
Kaisei Academy
Kaisei Academy is a prestigious Japanese boys' secondary school in Tokyo known for its rigorous academics and history of producing many prominent political and intellectual leaders.
-
E.
Koreiz
Koreiz is a resort settlement on the southern coast of Crimea, known for its seaside location and historic villas.
- 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ace714ec81909b0b1deaeac66be5 |
completed | March 1, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c01f00f48190b954db4a0cb5baa8 |
completed | March 4, 2026, 5:16 a.m. |
| NEDg | Description generation | batch_69a7c088506c81908a9e8ac91cb5b69d |
completed | March 4, 2026, 5:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7c10c8c2881908a739fe824b48782 |
completed | March 4, 2026, 5:20 a.m. |
Created at: March 1, 2026, 7:39 p.m.