Triple
T4252781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Furano |
E95894
|
entity |
| Predicate | touristAttraction |
P530
|
FINISHED |
| Object |
Farm Tomita
Farm Tomita is a famous flower farm in Furano, Hokkaido, best known for its expansive lavender fields and picturesque seasonal flower displays.
|
E423813
|
NE FINISHED |
How this triple was built (4 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: Farm Tomita | Statement: [Furano, touristAttraction, Farm Tomita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Farm Tomita Context triple: [Furano, touristAttraction, Farm Tomita]
-
A.
Tomomi
Tomomi is a Japanese given name that can be used for people of any gender.
-
B.
Tomoyuki
Tomoyuki is a Japanese masculine given name borne by various notable figures in fields such as the military, arts, and entertainment.
-
C.
Tomonaga
Tomonaga is a Japanese surname most notably borne by Sin-Itiro Tomonaga, a Nobel Prize–winning theoretical physicist known for his contributions to quantum electrodynamics.
-
D.
Itami
Itami is a city in Hyōgo Prefecture, Japan, known for hosting Osaka International Airport (commonly called Itami Airport).
-
E.
Toyooka
Toyooka is a city in northern Hyogo Prefecture, Japan, known for its stork conservation efforts, hot spring resort Kinosaki Onsen, and scenic coastal and rural landscapes.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Farm Tomita Triple: [Furano, touristAttraction, Farm Tomita]
Generated description
Farm Tomita is a famous flower farm in Furano, Hokkaido, best known for its expansive lavender fields and picturesque seasonal flower displays.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Farm Tomita Target entity description: Farm Tomita is a famous flower farm in Furano, Hokkaido, best known for its expansive lavender fields and picturesque seasonal flower displays.
-
A.
Tomomi
Tomomi is a Japanese given name that can be used for people of any gender.
-
B.
Tomoyuki
Tomoyuki is a Japanese masculine given name borne by various notable figures in fields such as the military, arts, and entertainment.
-
C.
Tomonaga
Tomonaga is a Japanese surname most notably borne by Sin-Itiro Tomonaga, a Nobel Prize–winning theoretical physicist known for his contributions to quantum electrodynamics.
-
D.
Itami
Itami is a city in Hyōgo Prefecture, Japan, known for hosting Osaka International Airport (commonly called Itami Airport).
-
E.
Toyooka
Toyooka is a city in northern Hyogo Prefecture, Japan, known for its stork conservation efforts, hot spring resort Kinosaki Onsen, and scenic coastal and rural landscapes.
- F. None of above. chosen
Provenance (5 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_69b3453f759881909b91f01a1e82c036 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34ebc98e08190915ac309a51ef87f |
completed | March 12, 2026, 11:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a8845e6081908bbf1aef2a2da754 |
completed | March 14, 2026, 6:27 p.m. |
| NEDg | Description generation | batch_69b5a8f374fc8190830286dfadc9bdbb |
completed | March 14, 2026, 6:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5a99a4a9c8190a7e9bbc119d8d775 |
completed | March 14, 2026, 6:31 p.m. |
Created at: March 12, 2026, 11:06 p.m.