Triple
T32823951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee Ufan |
E839503
|
entity |
| Predicate | dedicatedMuseumCountry |
P175524
|
FINISHED |
| Object | Japan |
—
|
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: Japan | Statement: [Lee Ufan, dedicatedMuseumCountry, Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dedicatedMuseumCountry Context triple: [Lee Ufan, dedicatedMuseumCountry, Japan]
-
A.
exhibitedCountry
Indicates the country in which something (such as an artwork, artifact, or exhibit) is or was displayed to the public.
-
B.
nationalMuseum
Indicates that an entity functions as a primary, officially recognized museum representing a nation at the national level.
-
C.
hasMemorialMuseum
Indicates that a memorial museum is dedicated to, associated with, or established in honor of a particular entity.
-
D.
hostCountryPavilion
Indicates that a pavilion is designated as the official exhibition space representing the host country at an event or exposition.
-
E.
hasMuseumAt
Indicates that a museum is located at or exists in a specified place or location.
- F. None of above. chosen
Provenance (4 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_69f3493df9008190a8f5d843dcd77704 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d210fc80819091ed8961aa2cddfb |
completed | May 3, 2026, 4:41 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
| PDg | Predicate description generation | batch_69f6d16b79dc8190ab0d4657f2ef9a5b |
completed | May 3, 2026, 4:39 a.m. |
Created at: May 1, 2026, 1:15 a.m.