Triple
T287354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ICANN Board of Directors |
E5912
|
entity |
| Predicate | hasPrimaryRole |
P88
|
FINISHED |
| Object | oversight of ICANN |
—
|
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: oversight of ICANN | Statement: [ICANN Board of Directors, hasPrimaryRole, oversight of ICANN]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryRole Context triple: [ICANN Board of Directors, hasPrimaryRole, oversight of ICANN]
-
A.
hasAuxiliaryRole
Indicates that an entity serves in a supporting or secondary capacity to another entity or primary role.
-
B.
hasPrimaryFunction
chosen
Indicates that one entity serves as the main or principal function or role of another entity.
-
C.
hasRole
Indicates that an entity occupies, performs, or is assigned a specific role or function in relation to another entity or context.
-
D.
hasPrimaryGoal
Indicates that an entity’s main or most important objective is the specified goal.
-
E.
hasPrimaryMeeting
Indicates that an entity is associated with its main or most important meeting, distinguishing it from other meetings it may have.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e2ddaa88190b08c40b5823f30a0 |
completed | Feb. 28, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69a25b7c1448819082064f474633acd5 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.