Triple
T16043372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lieutenant Governor's suite |
E389153
|
entity |
| Predicate | isWithinBuildingType |
P75382
|
FINISHED |
| Object | legislative building |
—
|
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: legislative building | Statement: [Lieutenant Governor's suite, isWithinBuildingType, legislative building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWithinBuildingType Context triple: [Lieutenant Governor's suite, isWithinBuildingType, legislative building]
-
A.
containsBuildingType
Indicates that a location or area includes at least one building of the specified type.
-
B.
belongsToBuildingType
chosen
Indicates that something is classified as being of a particular building type.
-
C.
appliedToBuildingType
Indicates that something (such as a rule, measure, or classification) is specifically applicable to a particular type of building.
-
D.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
E.
hasBuildingHeightType
Indicates the classification or type used to characterize the height of a building in the relationship.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1826f34c081908005bb736f1c485d |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.