Triple
T417426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bombardier M5000 |
E8024
|
entity |
| Predicate | lowFloorPercentage |
P14645
|
FINISHED |
| Object | partial low-floor |
—
|
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: partial low-floor | Statement: [Bombardier M5000, lowFloorPercentage, partial low-floor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowFloorPercentage Context triple: [Bombardier M5000, lowFloorPercentage, partial low-floor]
-
A.
numberOfBasementLevels
Indicates the total count of basement levels associated with a given structure or property.
-
B.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
C.
hasFloor
Indicates that one entity possesses, includes, or is associated with a particular floor or level within a structure.
-
D.
lowerValueIndicates
Indicates that a smaller numerical value of a property or measurement corresponds to a greater degree, better outcome, or stronger presence of the relevant characteristic.
-
E.
lowestPoint
Indicates that one entity is the point with the minimum vertical position or value relative to another entity or within a specified context.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd1ca148190a66bd8c5aad867d5 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb8545c8190a2b8517e7ed5b92e |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.