Triple
T3334547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gabba |
E70108
|
entity |
| Predicate | floodlighting |
P44709
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The Gabba, floodlighting, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floodlighting Context triple: [The Gabba, floodlighting, yes]
-
A.
floodlights
chosen
Indicates that one entity illuminates another with strong, focused artificial light, typically for visibility or emphasis.
-
B.
litOn
Indicates that one entity is illuminated or activated by a light source associated with another entity.
-
C.
floodEvent
Indicates an occurrence of a flooding event affecting a location, time period, or set of impacted entities.
-
D.
lightSourceGeneration
Indicates that an entity produces or emits light, serving as a source of illumination for other entities or the environment.
-
E.
fireAdaptation
Indicates that an entity possesses traits or mechanisms that enable it to survive, reproduce, or otherwise benefit in environments where fire occurs.
- 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_69ad85a24f208190bcf83131bfed3521 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1961b888190bda38ba301ddc51d |
completed | March 8, 2026, 5:27 p.m. |
| PD | Predicate disambiguation | batch_69ada42c2ba8819091136805ce17b39d |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.