Triple
T22688883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Stadium, Karachi |
E560993
|
entity |
| Predicate | lightingStandard |
P104734
|
FINISHED |
| Object | suitable for day-night matches |
—
|
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: suitable for day-night matches | Statement: [National Stadium, Karachi, lightingStandard, suitable for day-night matches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightingStandard Context triple: [National Stadium, Karachi, lightingStandard, suitable for day-night matches]
-
A.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
B.
lightingColor
Indicates the color or hue of the lighting applied to or associated with an entity.
-
C.
laterLightingType
Indicates that one lighting type occurs or is applied after another in time.
-
D.
lightingCharacteristic
Indicates the specific qualities or properties of how something is lit, such as brightness, color, direction, or style of illumination.
-
E.
lightingRecommended
chosen
Indicates that a particular lighting setup or condition is advised as suitable or optimal for a given context or use.
- 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789931148190925ce9038c16413b |
completed | April 29, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:13 p.m.