Triple
T20920228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best Denki Stadium |
E515186
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Level-5 Stadium |
—
|
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: Level-5 Stadium | Statement: [Best Denki Stadium, formerName, Level-5 Stadium]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Level-5 Stadium Context triple: [Best Denki Stadium, formerName, Level-5 Stadium]
-
A.
Level-5 Stadium
chosen
Level-5 Stadium is a football stadium in Fukuoka, Japan, formerly used as the home ground of the J.League club Avispa Fukuoka.
-
B.
Loveless Stadium
Loveless Stadium is the home softball venue for the University of North Texas Mean Green athletic program.
-
C.
Tenri Stadium
Tenri Stadium is a multi-purpose sports venue in Tenri, Nara Prefecture, Japan, primarily used for athletics and football matches.
-
D.
Setsoto Stadium
Setsoto Stadium is a multi-purpose national sports venue in Maseru, Lesotho, primarily used for football matches and major public events.
-
E.
Edogawa Stadium
Edogawa Stadium is a multi-purpose sports venue in Tokyo, Japan, primarily used for athletics and football matches.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec677338819081410cbaa2846260 |
completed | April 21, 2026, 3:17 a.m. |
Created at: April 16, 2026, 12:48 p.m.