Triple
T17550412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gratte-Ciel |
E427444
|
entity |
| Predicate | hasBuildingHeightCategory |
P3373
|
FINISHED |
| Object | mid-rise to high-rise |
—
|
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: mid-rise to high-rise | Statement: [Gratte-Ciel, hasBuildingHeightCategory, mid-rise to high-rise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingHeightCategory Context triple: [Gratte-Ciel, hasBuildingHeightCategory, mid-rise to high-rise]
-
A.
hasBuildingHeightType
chosen
Indicates the classification or type used to characterize the height of a building in the relationship.
-
B.
buildingHeightContext
Indicates the contextual or situational factors under which a building’s height is defined, measured, or interpreted.
-
C.
buildingHeight
Indicates the vertical extent or height measurement of a building.
-
D.
hasCliffHeightCategory
Indicates the categorized height range of a cliff associated with an entity.
-
E.
buildingHeightCharacteristic
Indicates the specific height-related property or measurement that characterizes a building.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e454656dc08190bba85b93bd07b0a2 |
completed | April 19, 2026, 4:04 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fb39948190a82a597c5bac5c57 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.