Triple
T10761288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape to Cairo Railway project |
E253831
|
entity |
| Predicate | obstacle |
P52690
|
FINISHED |
| Object | political fragmentation of Africa |
—
|
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: political fragmentation of Africa | Statement: [Cape to Cairo Railway project, obstacle, political fragmentation of Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: obstacle Context triple: [Cape to Cairo Railway project, obstacle, political fragmentation of Africa]
-
A.
obstacles
chosen
Indicates that one entity presents barriers, hindrances, or impediments that block or restrict another entity’s progress, action, or interaction.
-
B.
isBarrierTo
Indicates that one entity obstructs, prevents, or significantly hinders another entity from occurring, progressing, or being accessed.
-
C.
isDifficultToAccessBecauseOf
Indicates that something is hard to reach, obtain, or use due to a specified obstacle, condition, or circumstance.
-
D.
trap
Indicates that an entity captures, confines, or ensnares another entity, typically preventing its escape or movement.
-
E.
hasObjectiveHazards
Indicates that an entity is associated with concrete, externally verifiable dangers or risks.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d731a230ac8190920439076aaeb91e |
completed | April 9, 2026, 4:57 a.m. |
| PD | Predicate disambiguation | batch_69d6f311529c819080ca5493d55d6050 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:16 p.m.