Triple
T13316553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harukas 300 |
E317201
|
entity |
| Predicate | locatedInSkyscraperHeightClass |
P32819
|
FINISHED |
| Object | super-tall skyscraper |
—
|
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: super-tall skyscraper | Statement: [Harukas 300, locatedInSkyscraperHeightClass, super-tall skyscraper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInSkyscraperHeightClass Context triple: [Harukas 300, locatedInSkyscraperHeightClass, super-tall skyscraper]
-
A.
locatedInSkyscraper
chosen
Indicates that one entity is physically situated within or inside a skyscraper.
-
B.
locatedInSkyscraperDistrict
Indicates that an entity is situated within a district or area characterized by skyscrapers.
-
C.
isSkyscraperIn
Indicates that a skyscraper is located within or belongs to a specified geographic area or place.
-
D.
tallestBuildingIn
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
E.
buildingHeightContext
Indicates the contextual or situational factors under which a building’s height is defined, measured, or interpreted.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6babd88190a5d529df9584b9a4 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:29 p.m.