Triple
T2579424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oahu |
E57052
|
entity |
| Predicate | hasNicknameUsage |
P13305
|
FINISHED |
| Object | widely used in tourism |
—
|
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: widely used in tourism | Statement: [Oahu, hasNicknameUsage, widely used in tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNicknameUsage Context triple: [Oahu, hasNicknameUsage, widely used in tourism]
-
A.
isNickname
Indicates that one name is an informal or alternative name commonly used to refer to the same person or entity as another name.
-
B.
hasGivenNameUsage
Indicates that an entity is associated with a particular way or context in which its given name is used.
-
C.
nameUsedIn
chosen
Indicates that a particular name is employed or referenced within a specified context, work, or usage setting.
-
D.
nameUsedBy
Indicates that a particular name is employed or referenced by a specific entity.
-
E.
hasSupporterNickname
Indicates that an entity is associated with a nickname or informal name used specifically by its supporters or fans.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3a9fd3c8190a521931e40cd801c |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0cfeae08190aed03866ba071c5c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.