Triple
T5985107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Tokyo fire whirl at Rikugun Honjo Hifukusho |
E133207
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Honjo |
E296744
|
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: Honjo | Statement: [Great Tokyo fire whirl at Rikugun Honjo Hifukusho, location, Honjo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Honjo Context triple: [Great Tokyo fire whirl at Rikugun Honjo Hifukusho, location, Honjo]
-
A.
Honjo
chosen
Honjo is a historic district in Tokyo known for its traditional shitamachi atmosphere and close ties to the Sumida River area.
-
B.
Hōshō
Hōshō was the Imperial Japanese Navy’s pioneering aircraft carrier and the world’s first purpose-built carrier to enter service.
-
C.
Gotō
Gotō is a Japanese surname borne by various notable figures in politics, business, and the arts.
-
D.
Hanazono
Hanazono is a popular ski and outdoor recreation area within the Niseko resort region of Hokkaido, Japan, known for its powder snow and winter sports facilities.
-
E.
Keiyo
Keiyo is a Southern Nilotic language spoken primarily by the Keiyo people of Kenya’s Rift Valley region.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04a6dcaf08190bac27c7042e65e07 |
completed | March 22, 2026, 8 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1413ca5f88190b0dab30bde04af4c |
completed | March 23, 2026, 1:33 p.m. |
Created at: March 22, 2026, 4:04 p.m.