Triple
T2875745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tohoku University |
E56872
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | Tohoku U |
E56872
|
NE FINISHED |
How this triple was built (2 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: Tohoku U | Statement: [Tohoku University, hasAbbreviation, Tohoku U]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tohoku U Context triple: [Tohoku University, hasAbbreviation, Tohoku U]
-
A.
Tohoku U
chosen
Tohoku U is a leading national research university in Sendai, Japan, renowned for its engineering, science, and materials research.
-
B.
Tohoku
Tohoku is the northeastern region of Japan’s main island, known for its rural landscapes, harsh winters, and rich traditional culture.
-
C.
Yamagata
Yamagata is a city in northern Japan that serves as the capital of Yamagata Prefecture, known for its hot springs, winter sports, and cherry production.
-
D.
Aomori
Aomori is a city in northern Japan known as the capital of Aomori Prefecture and for its Nebuta summer festival, snowy winters, and apple production.
-
E.
Settsu
Settsu is a city in Osaka Prefecture, Japan, known as part of the Osaka metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ab4a4ced288190ab6d3e062d10f7f6 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abe004a64481908f1897d9054a7368 |
completed | March 7, 2026, 8:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01dbb28588190ba2daae192744908 |
completed | March 10, 2026, 1:33 p.m. |
Created at: March 6, 2026, 10:03 p.m.