Triple
T10489529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chad–Sudan border |
E247377
|
entity |
| Predicate | hasCrossBorderRaids |
P94593
|
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: [Chad–Sudan border, hasCrossBorderRaids, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossBorderRaids Context triple: [Chad–Sudan border, hasCrossBorderRaids, true]
-
A.
crossesBorderOf
Indicates that one entity passes from one side of the boundary of another entity (typically a region or area) to the other side, traversing its border.
-
B.
hasBorderWithNonSovereignEntity
Indicates that one entity shares a land or maritime border with a political or territorial unit that is not fully sovereign.
-
C.
hasBorderCrossing
Indicates that there exists a point or facility where movement or transit is possible between the boundaries of two adjacent regions or jurisdictions.
-
D.
hasCrossBorderTies
Indicates that there exists a relationship or connection that extends across national or jurisdictional boundaries between the involved entities.
-
E.
locatedNearStateBorderWith
Indicates that one entity is situated geographically close to the border of a specified state.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5097ca5c081908b47a08ca7885650 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8a30848190b33cf43f005a028e |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d5092af880819082b42c0a68e45c5f |
completed | April 7, 2026, 1:39 p.m. |
Created at: April 6, 2026, 12:23 p.m.