Triple
T14852888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A3 |
E349273
|
entity |
| Predicate | connectsCapitalToBorder |
P115873
|
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: [A3, connectsCapitalToBorder, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsCapitalToBorder Context triple: [A3, connectsCapitalToBorder, true]
-
A.
connectsCountryBorder
Indicates that one entity forms a direct land or maritime border connection with a specified country.
-
B.
connectsCoastToBorder
Indicates a relationship where something (such as a route, feature, or boundary) links a coastal area directly to a national or regional border.
-
C.
hasCapitalConnected
Indicates that there is a direct connection or linkage between an entity and its capital city.
-
D.
regionCapitalConnected
Indicates that a capital city is directly connected (e.g., by transport or infrastructure) to its surrounding region.
-
E.
crossBorderFacilityConnectsTo
Indicates that a cross-border facility provides a direct physical or operational connection between two locations or infrastructures across a border.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded441e70881909bbf62b66d932aff |
completed | April 14, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:54 a.m.