Triple
T4102350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nevada–Utah state line |
E87968
|
entity |
| Predicate | isMostlyStraight |
P53380
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Nevada–Utah state line, isMostlyStraight, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMostlyStraight Context triple: [Nevada–Utah state line, isMostlyStraight, true]
-
A.
hasStraightLines
Indicates that the related entity possesses or is characterized by straight, non-curved lines.
-
B.
hasMainStraightLengthKm
Indicates the length in kilometers of the primary or main straight segment associated with an entity.
-
C.
mainStraightLengthM
Indicates the length, measured in meters, of the main straight segment (typically of a track, road, or similar linear feature).
-
D.
isMostly
Indicates that one entity constitutes the greater part or majority of another entity in amount, extent, or composition.
-
E.
circuitHasLongStraight
Indicates that a circuit includes at least one long, uninterrupted straight section.
- 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_69aed94564cc8190a9c1457daedb6e7f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd1012208190ab0980c661d6bc41 |
completed | March 9, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69aef90b2ef08190ae84febfd69dd48b |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa5c52648190b001027f4dba75cb |
completed | March 9, 2026, 4:50 p.m. |
Created at: March 9, 2026, 3:40 p.m.