Triple
T9723893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Settsu |
E235551
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Takatsuki |
E9377
|
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: Takatsuki | Statement: [Settsu, locatedNear, Takatsuki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Takatsuki Context triple: [Settsu, locatedNear, Takatsuki]
-
A.
Takatsuki
chosen
Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
-
B.
Wakatsuki
Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
-
C.
Mikasuki
Mikasuki is a Native American language of the Muskogean family, traditionally spoken by the Miccosukee and some Seminole people in the southeastern United States.
-
D.
Totsukawa
Totsukawa is a remote mountainous village in Nara Prefecture, Japan, known for its hot springs, suspension bridges, and scenic river valleys.
-
E.
Suzuya
Suzuya is a Japanese Mogami-class heavy cruiser of the Imperial Japanese Navy that served during World War II.
- 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_69ca84d0123c819096f9dc3b6abb0881 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e77096481908ffd315fecb1d5ec |
completed | April 1, 2026, 10:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e482d55a04819090d95f7a4abb6e29 |
completed | April 19, 2026, 7:23 a.m. |
Created at: March 30, 2026, 8:21 p.m.