Triple
T1388884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape of Good Hope |
E29908
|
entity |
| Predicate | seaReputation |
P28205
|
FINISHED |
| Object | rough seas |
—
|
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: rough seas | Statement: [Cape of Good Hope, seaReputation, rough seas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seaReputation Context triple: [Cape of Good Hope, seaReputation, rough seas]
-
A.
associatedWithReputation
Indicates a relationship where an entity is linked to, influenced by, or characterized in terms of another entity’s reputation or perceived standing.
-
B.
shipRepresents
Indicates that one entity (typically a ship) serves as a symbol, stand-in, or representation for another entity, concept, or group.
-
C.
reputationBuiltFor
Indicates that one entity has established or developed a reputation specifically for or in relation to another entity.
-
D.
tacticalReputation
Indicates the perceived level of skill, reliability, or effectiveness an entity has in planning and executing tactics within a given context.
-
E.
regionalReputation
Indicates the recognition or standing an entity has within a specific geographic region based on its performance, influence, or perceived quality.
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c35ce48c81909aaad7dfa2df63fa |
completed | March 1, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69a4beffcf808190ab4cd0271257ce63 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c2f16ae081908c92792253f3eb4b |
completed | March 1, 2026, 10:51 p.m. |
Created at: March 1, 2026, 7:59 p.m.