Triple
T14796173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sayama |
E347782
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Tokorozawa |
—
|
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: Tokorozawa | Statement: [Sayama, borderedBy, Tokorozawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tokorozawa Context triple: [Sayama, borderedBy, Tokorozawa]
-
A.
Tokorozawa
chosen
Tokorozawa is a commuter city in the Greater Tokyo area of Japan, known for its residential neighborhoods, aviation history, and role as a transport hub in southern Saitama.
-
B.
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.
-
C.
Fujieda
Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
-
D.
Takasaki
Takasaki is a city in Japan’s Gunma Prefecture known for its Daruma doll production and as a regional commercial and transportation hub.
-
E.
Yokkaichi
Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd5fdd548190a2ee5e668c2b20b4 |
completed | April 14, 2026, 11:27 p.m. |
Created at: April 10, 2026, 1:31 a.m.