Triple
T12252412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gelora Bung Tomo Stadium |
E292004
|
entity |
| Predicate | hasStandsRoof |
P78546
|
FINISHED |
| Object | partially covered stands |
—
|
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: partially covered stands | Statement: [Gelora Bung Tomo Stadium, hasStandsRoof, partially covered stands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandsRoof Context triple: [Gelora Bung Tomo Stadium, hasStandsRoof, partially covered stands]
-
A.
hasRoofShape
Indicates that one entity possesses or is characterized by a specific shape or form of roof.
-
B.
hasTypeOfRoof
chosen
Indicates that an entity possesses or is characterized by a specific kind or style of roof.
-
C.
hasRooftop
Indicates that one entity possesses or is equipped with a rooftop as a structural feature.
-
D.
hasIconicRoofShape
Indicates that an entity possesses a roof with a distinctive, widely recognized, or characteristic shape.
-
E.
hasDomeOrRoofAccess
Indicates that an entity has access to, or the ability to reach or use, a dome or roof area associated with 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91d38ee10819093ed41d2954bf4ef |
completed | April 10, 2026, 3:54 p.m. |
| PD | Predicate disambiguation | batch_69d91c46dcd88190a263db30804bff36 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.