Triple
T25345251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roxa |
E635527
|
entity |
| Predicate | nearbyMajorLandmass |
P167255
|
FINISHED |
| Object | mainland Guinea-Bissau |
—
|
NE NERFINISHED |
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: mainland Guinea-Bissau | Statement: [Roxa, nearbyMajorLandmass, mainland Guinea-Bissau]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyMajorLandmass Context triple: [Roxa, nearbyMajorLandmass, mainland Guinea-Bissau]
-
A.
nearestLandmass
Indicates that one landmass is the closest geographically to another specified point or landmass.
-
B.
nearestLargeBodyOfWater
Indicates the closest significant body of water in proximity to a given location or entity.
-
C.
onLandmass
Indicates that one entity is physically located on or within the boundaries of a specified landmass.
-
D.
nearestMainlandPoint
Indicates the relationship where a location is associated with the closest point on the mainland to that location.
-
E.
majorLandmasses
Indicates that the related entities are the primary, large continuous expanses of land on a planetary surface.
- 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_69e75a9ac5d881909387ed766e20cd47 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f66a6468ec8190a43ed6cd8c797f42 |
completed | May 2, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 21, 2026, 1:34 p.m.