Triple
T27188594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palikur people |
E683403
|
entity |
| Predicate | borderRegionPeople |
P30106
|
FINISHED |
| Object | Brazil–French Guiana border |
—
|
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: Brazil–French Guiana border | Statement: [Palikur people, borderRegionPeople, Brazil–French Guiana border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderRegionPeople Context triple: [Palikur people, borderRegionPeople, Brazil–French Guiana border]
-
A.
borderRegionPresence
chosen
Indicates the presence or occurrence of something within or along a border region between areas or territories.
-
B.
borderRegion
Indicates a region that lies along or near the boundary separating two distinct geographic or political areas.
-
C.
borderRegime
Indicates the type, rules, or control system governing how movement or interaction is managed across a border between entities.
-
D.
borderStationFor
Indicates that a particular border station serves, monitors, or is responsible for a specific border crossing or boundary segment.
-
E.
borderStateNearby
Indicates that one state is geographically close to, but does not necessarily directly touch, the border of another state.
- F. None of above.
Provenance (3 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_69eefad140408190b8586fdebcf9af46 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
Created at: April 27, 2026, 9:31 a.m.