Triple
T7363807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gelora Bung Karno Stadium |
E169815
|
entity |
| Predicate | safetyUpgrade |
P33946
|
FINISHED |
| Object | installation of individual seats |
—
|
LITERAL 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: installation of individual seats | Statement: [Gelora Bung Karno Stadium, safetyUpgrade, installation of individual seats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyUpgrade Context triple: [Gelora Bung Karno Stadium, safetyUpgrade, installation of individual seats]
-
A.
safetyChangesImplemented
chosen
Indicates that specific safety-related modifications or measures have been put into effect.
-
B.
safetyBenefit
Indicates that one entity provides, contributes to, or results in an improvement in the safety or risk reduction experienced by another entity.
-
C.
safetyCategory
Indicates the classification of something according to its level or type of safety.
-
D.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
E.
upgradeOf
Indicates that one entity is a newer, improved, or more advanced version of another entity.
- 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_69c68a5ade988190885b7175f63b7534 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26d6d6081909c7272a9ccae0d97 |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f02d36108190bcb34a95e6a30bd7 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:06 p.m.