Triple
T6949040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glass Floor at CN Tower |
E160873
|
entity |
| Predicate | locatedOnLevel |
P74241
|
FINISHED |
| Object | LookOut Level and Glass Floor level |
—
|
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: LookOut Level and Glass Floor level | Statement: [Glass Floor at CN Tower, locatedOnLevel, LookOut Level and Glass Floor level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedOnLevel Context triple: [Glass Floor at CN Tower, locatedOnLevel, LookOut Level and Glass Floor level]
-
A.
locatedIn
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
B.
locatedUnder
Indicates that one entity is positioned directly or generally beneath another entity in space.
-
C.
locatedOnTerrain
Indicates that one entity is physically situated on or atop a particular terrain surface.
-
D.
locatedAlong
Indicates that one entity is situated adjacent to, or running beside, the length or course of another linear feature (such as a road, river, or railway).
-
E.
locatedOnBody
Indicates that one entity is physically situated on the surface or external part of another entity’s body.
- 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_69c68850419081909fb426b8f5a304c7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dacca12481908942ba793a104cc3 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bf0a7c8190b5ed4aca22ba9b97 |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6dacb524c81909aade2282a4c0c01 |
completed | March 27, 2026, 7:30 p.m. |
Created at: March 27, 2026, 2:28 p.m.