Triple
T1983974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert C. Weaver Federal Building |
E43095
|
entity |
| Predicate | floorCountAboveGround |
P1514
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Robert C. Weaver Federal Building, floorCountAboveGround, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floorCountAboveGround Context triple: [Robert C. Weaver Federal Building, floorCountAboveGround, 10]
-
A.
floorCount
chosen
Indicates the number of floors or levels that a building or structure has.
-
B.
floorCountIncludingBasement
Indicates the total number of floors in a building, counting all above-ground levels plus any basement levels.
-
C.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
D.
hasGroundFloor
Indicates that a building or structure includes a ground-level floor as part of its layout or design.
-
E.
numberOfBasementLevels
Indicates the total count of basement levels associated with a given structure or property.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb96f932881908bebfc4176fda7c0 |
completed | March 7, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69abb798d288819083132cf14605bd02 |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.