Triple
T1209753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cairo Tower |
E25970
|
entity |
| Predicate | hasNightLighting |
P1280
|
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: [Cairo Tower, hasNightLighting, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNightLighting Context triple: [Cairo Tower, hasNightLighting, yes]
-
A.
hasLighting
chosen
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
B.
lightRange
Indicates the distance or area over which a light source effectively emits or illuminates.
-
C.
lightLevel
Indicates the intensity or amount of light present in a given context or environment.
-
D.
hasTorchRelay
Indicates that an event or entity includes or is associated with a torch relay as part of its activities or proceedings.
-
E.
hasRunwayLighting
Indicates that a runway is equipped with lighting systems to aid visibility and operations, typically during low-light or night conditions.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bde30ce08190ab60a181ad2d321d |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6078088190ba0221ae3368416c |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.