Triple
T11092774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takamatsu Port |
E262296
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Takamatsu city center |
E210953
|
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: Takamatsu city center | Statement: [Takamatsu Port, near, Takamatsu city center]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Takamatsu city center Context triple: [Takamatsu Port, near, Takamatsu city center]
-
A.
Takamatsu
chosen
Takamatsu is a coastal city in Japan’s Kagawa Prefecture on the island of Shikoku, known as a regional transport hub and gateway to the Seto Inland Sea.
-
B.
Yokohama city center
Yokohama city center is the main urban and commercial hub of Yokohama, known for its modern skyline, waterfront districts, and major shopping and business areas.
-
C.
Himeji
Himeji is a historic Japanese city best known for Himeji Castle, a UNESCO World Heritage Site and one of Japan’s most iconic and well-preserved feudal castles.
-
D.
Ōsaki
Ōsaki is a major commercial and business district in Tokyo known for its high-rise office complexes and convenient rail connections.
-
E.
Toyokawa
Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799ec6564819097624195d0cd9093 |
completed | April 9, 2026, 12:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d69c8b4819092614e83e855430e |
completed | April 19, 2026, 1:18 a.m. |
Created at: April 8, 2026, 9:27 p.m.