Triple
T12594591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Tsukuba |
E300701
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Tsukuba City |
—
|
NE NERFINISHED |
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: Tsukuba City | Statement: [Mount Tsukuba, locatedNear, Tsukuba City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsukuba City Context triple: [Mount Tsukuba, locatedNear, Tsukuba City]
-
A.
Tsukuba
chosen
Tsukuba is a planned science and technology city in Ibaraki Prefecture, Japan, known for its research institutions and role as the host of the 1985 World Exposition.
-
B.
Ibaraki City
Ibaraki City is a suburban city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
-
C.
Takasaki
Takasaki is a city in Japan’s Gunma Prefecture known for its Daruma doll production and as a regional commercial and transportation hub.
-
D.
Ueda City
Ueda City is a historic regional center in eastern Nagano Prefecture, Japan, known for Ueda Castle, samurai heritage, and its surrounding mountainous scenery.
-
E.
Akishima
Akishima is a city in western Tokyo, Japan, known as part of the Tama area and characterized by its residential neighborhoods and light industry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954cde3c0819094e74413d6dcf548 |
completed | April 10, 2026, 7:51 p.m. |
Created at: April 9, 2026, 5:08 p.m.