Triple
T23835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empire State Building |
E472
|
entity |
| Predicate | floorArea |
P175
|
FINISHED |
| Object | approximately 2088791 square feet |
—
|
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: approximately 2088791 square feet | Statement: [Empire State Building, floorArea, approximately 2088791 square feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floorArea Context triple: [Empire State Building, floorArea, approximately 2088791 square feet]
-
A.
area
chosen
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
B.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
C.
numberOfBasementLevels
Indicates the total count of basement levels associated with a given structure or property.
-
D.
building
Indicates that one entity constructs, assembles, or develops another entity, typically over a period of time.
-
E.
residence
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.