Triple
T14835112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Porto Praya |
E348810
|
entity |
| Predicate | primaryObjectiveOfFrench |
P116017
|
FINISHED |
| Object | reach the Cape of Good Hope |
—
|
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: reach the Cape of Good Hope | Statement: [Battle of Porto Praya, primaryObjectiveOfFrench, reach the Cape of Good Hope]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryObjectiveOfFrench Context triple: [Battle of Porto Praya, primaryObjectiveOfFrench, reach the Cape of Good Hope]
-
A.
objectiveOfFrance
Indicates that something is an objective, goal, or aim pursued by France.
-
B.
FrenchObjective
Indicates that an entity serves as the goal, target, or object of an action or relation specifically within a French linguistic or contextual framework.
-
C.
primaryFrenchDestination
Indicates that one entity is the main or most significant travel destination in France for another entity.
-
D.
significanceForFrance
Indicates that something holds particular importance, impact, or relevance specifically in the context of France.
-
E.
notableObjectiveInNormandy
Indicates that an entity had a significant goal, target, or mission specifically within the context of the Normandy campaign or region.
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded076ac9c8190a05cabec5e87d207 |
completed | April 14, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69de8c13418c819088ff9905ace1416a |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de90806f3881908fcbfec5bd4ab4d2 |
completed | April 14, 2026, 7:07 p.m. |
Created at: April 10, 2026, 1:52 a.m.