Triple
T21544074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sabanagrande |
E531569
|
entity |
| Predicate | sharesBorderWithDepartment |
P144171
|
FINISHED |
| Object | departments of Honduras |
—
|
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: departments of Honduras | Statement: [Sabanagrande, sharesBorderWithDepartment, departments of Honduras]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesBorderWithDepartment Context triple: [Sabanagrande, sharesBorderWithDepartment, departments of Honduras]
-
A.
sharesBorderWithInOfficeContext
Indicates that two offices or workspaces are directly adjacent to each other, sharing a common boundary or wall within a workplace layout.
-
B.
sharesDepartmentWith
Indicates that two entities work in or are associated with the same department within an organization.
-
C.
sharesBorderingNetworkWith
Indicates that two entities are connected through adjacent or directly neighboring positions within the same network structure.
-
D.
sharesDivisionWith
Indicates that two entities belong to or operate within the same organizational division.
-
E.
sharesCorridorWith
Indicates that two entities are located along or connected by the same corridor or passageway.
- 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_69e0c45f17148190949c330ab9c27706 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeb58d66ec8190b654a46932c841d3 |
completed | April 27, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69e6320766308190ba5dca2f7c826aa4 |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e633bf34c481909925d8dc1a633a65 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 16, 2026, 6:28 p.m.