Triple
T22004612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soldier Summit route |
E543418
|
entity |
| Predicate | hasRailroadGrade |
P121368
|
FINISHED |
| Object | approximately 2.4 percent on west side (historically) |
—
|
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 2.4 percent on west side (historically) | Statement: [Soldier Summit route, hasRailroadGrade, approximately 2.4 percent on west side (historically)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailroadGrade Context triple: [Soldier Summit route, hasRailroadGrade, approximately 2.4 percent on west side (historically)]
-
A.
railroadGrade
Indicates that one entity is at the elevation or level of a railroad track or crossing relative to another entity.
-
B.
hasRailLevel
Indicates that one entity possesses, is assigned, or is associated with a specific rail-related level or classification in relation to another entity.
-
C.
usesRailGauge
Indicates that one entity (typically a railway system or line) operates using the specified rail gauge measurement of the other entity.
-
D.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
-
E.
railwayGradient
chosen
Indicates the slope or steepness of a railway track along its route.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1276d81e4819083a40e51249e7fd7 |
completed | April 28, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e6f62dc9d88190ae387f145f9528de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:20 p.m.