Triple
T11934405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sendagi |
E284000
|
entity |
| Predicate | administrativeDivision |
P747
|
FINISHED |
| Object | Bunkyō City |
E366668
|
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: Bunkyō City | Statement: [Sendagi, administrativeDivision, Bunkyō City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bunkyō City Context triple: [Sendagi, administrativeDivision, Bunkyō City]
-
A.
Bunkyō City
chosen
Bunkyō City is a special ward in central Tokyo, Japan, known for its universities, historic temples, and quiet residential neighborhoods.
-
B.
Sumida City
Sumida City is a special ward of Tokyo, Japan, known for landmarks such as the Tokyo Skytree and its traditional downtown neighborhoods.
-
C.
Shibuya City
Shibuya City is a major commercial and entertainment district in central Tokyo, Japan, famous for its bustling scramble crossing, youth culture, and fashion scene.
-
D.
Shiojiri City
Shiojiri City is a regional city in central Japan known for its location in Nagano Prefecture’s mountainous inland area and its role as a transportation and agricultural hub.
-
E.
Osaki City
Osaki City is a regional city in northeastern Japan known for its agricultural production, hot springs, and historical sites.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90306fcf48190a963d2d1932288d1 |
completed | April 10, 2026, 2:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a014132570081909fab220c002c2f10 |
completed | May 11, 2026, 2:38 a.m. |
Created at: April 8, 2026, 9:45 p.m.