Triple
T4102356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nevada–Utah state line |
E87968
|
entity |
| Predicate | hasNoInternationalCrossing |
P53383
|
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, hasNoInternationalCrossing, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoInternationalCrossing Context triple: [Nevada–Utah state line, hasNoInternationalCrossing, true]
-
A.
hasBorderCrossing
Indicates that there exists a point or facility where movement or transit is possible between the boundaries of two adjacent regions or jurisdictions.
-
B.
hasBorderCrossingFunction
Indicates that an entity serves as a location or facility where people, goods, or vehicles can legally cross a border between jurisdictions.
-
C.
hasDomesticTerminal
Indicates that a transportation facility, typically an airport, includes a terminal dedicated to domestic (within-country) travel operations.
-
D.
nearInternationalBoundary
Indicates that one entity is located close to an international boundary separating two or more countries.
-
E.
hasCrossBorderCommuting
Indicates that there is a regular pattern of commuting across national borders between the related entities.
- 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.