Triple
T37249789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hall A |
E923957
|
entity |
| Predicate | isMainAuditoriumOf |
P187341
|
FINISHED |
| Object | Tokyo International Forum |
—
|
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: Tokyo International Forum | Statement: [Hall A, isMainAuditoriumOf, Tokyo International Forum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMainAuditoriumOf Context triple: [Hall A, isMainAuditoriumOf, Tokyo International Forum]
-
A.
hasAuditorium
Indicates that one entity possesses or includes an auditorium as part of its facilities.
-
B.
auditoriumType
Indicates the specific kind or category of auditorium associated with an entity.
-
C.
isLargestHallOf
chosen
Indicates that one entity is the largest hall belonging to, contained within, or associated with another entity.
-
D.
shapeOfOriginalAuditorium
Indicates the geometric form or layout that characterized the auditorium in its original design or construction.
-
E.
hasGrandHall
Indicates that an entity possesses or includes a grand hall as part of its structure or facilities.
- F. None of above.
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_69f76eaabb4c819093b751b139dad551 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:15 p.m.