Triple
T28019842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K Track |
E707654
|
entity |
| Predicate | railProfile |
P160250
|
FINISHED |
| Object | flat-bottom rail profile |
—
|
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: flat-bottom rail profile | Statement: [K Track, railProfile, flat-bottom rail profile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railProfile Context triple: [K Track, railProfile, flat-bottom rail profile]
-
A.
railProfile
chosen
Indicates that one entity specifies the cross-sectional shape or profile characteristics of a rail associated with another entity.
-
B.
railInterface
Indicates a connection or interaction between entities via a rail-based system or interface.
-
C.
railSystemType
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
-
D.
railwayLineType
Indicates the specific kind or classification of a railway line associated with an entity (e.g., main line, branch line, high-speed line).
-
E.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced 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_69ef96baf3a881909a2b63844185dddd |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f63c0a2d208190b8a611be07ac5977 |
completed | May 2, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69f63710d17c819084cfe96e6df334fd |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 8:09 p.m.