Triple
T25929070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gulf of Guinea islands |
E653384
|
entity |
| Predicate | hasHumanActivities |
P162127
|
FINISHED |
| Object | fishing |
—
|
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: fishing | Statement: [Gulf of Guinea islands, hasHumanActivities, fishing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHumanActivities Context triple: [Gulf of Guinea islands, hasHumanActivities, fishing]
-
A.
hasHumanActivities
chosen
Indicates that certain human actions, behaviors, or practices are present, performed, or associated with a given entity.
-
B.
hasActivityIn
Indicates that an entity engages in or performs a particular activity within a specified context, location, or domain.
-
C.
has activity
Indicates that one entity performs, exhibits, or is engaged in a particular action, behavior, or process associated with another entity.
-
D.
hasVisitorActivities
Indicates that a place or entity offers or is associated with specific activities available for visitors to engage in.
-
E.
hasPopularActivity
Indicates that an entity is associated with an activity that is widely favored, frequently engaged in, or well-liked by many people.
- 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_69e7ab3eb9b881909c1390690551f868 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f627aedf548190bc9f53c8a2d67b50 |
completed | May 2, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69f623a4e1048190bbb8dd1253fdcee9 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 22, 2026, 8:36 a.m.