Triple
T3025922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galle International Stadium |
E82573
|
entity |
| Predicate | floodlights |
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: [Galle International Stadium, floodlights, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floodlights Context triple: [Galle International Stadium, floodlights, yes]
-
A.
hasRunwayLighting
Indicates that a runway is equipped with lighting systems to aid visibility and operations, typically during low-light or night conditions.
-
B.
numberOfLights
Indicates the quantity of lights associated with or present on a given entity.
-
C.
led
Indicates that one entity guided, directed, or was in charge of another entity or activity, typically over a period of time.
-
D.
lightSourceFor
Indicates that one entity serves as the source of illumination for another entity.
-
E.
hasNumberOfMainLights
Indicates the relationship that specifies how many primary or main lights are associated with an entity.
- F. None of above. chosen
Provenance (4 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_69ad8b1fb34081908c1b873e2b7273e1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9abc78b48190a5283e7407a78fe7 |
completed | March 8, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69ad961c430c8190ac48f2e3c7e7c649 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f6af3881909f4547967384114c |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 3 p.m.