Triple
T12947777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisiana State Capitol |
E309812
|
entity |
| Predicate | floorCountRank |
P107637
|
FINISHED |
| Object | tallest capitol building in the United States |
—
|
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: tallest capitol building in the United States | Statement: [Louisiana State Capitol, floorCountRank, tallest capitol building in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floorCountRank Context triple: [Louisiana State Capitol, floorCountRank, tallest capitol building in the United States]
-
A.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
B.
floorCountApproximate
Indicates an approximate or estimated number of floors associated with a building or structure.
-
C.
floorHeight
Indicates the vertical elevation or level at which a particular floor is positioned within a structure.
-
D.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
E.
floorCountOfSurroundingBuildings
Indicates the number of floors in the buildings that are located around or near a given reference building or area.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97e5811f481908178fac6d2e0efcd |
completed | April 10, 2026, 10:48 p.m. |
Created at: April 9, 2026, 5:43 p.m.