Triple
T21890862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wasilla, Alaska |
E540539
|
entity |
| Predicate | roleForNotableResident |
P12885
|
FINISHED |
| Object | Sarah Palin served as mayor of Wasilla |
—
|
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: Sarah Palin served as mayor of Wasilla | Statement: [Wasilla, Alaska, roleForNotableResident, Sarah Palin served as mayor of Wasilla]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleForNotableResident Context triple: [Wasilla, Alaska, roleForNotableResident, Sarah Palin served as mayor of Wasilla]
-
A.
hasNotableResident
Indicates that an entity is or has been a well-known or distinguished resident of a particular place or location.
-
B.
ethnicRole
Indicates a role, function, or social position that is specifically associated with or defined by an entity’s ethnicity.
-
C.
namedPersonRole
chosen
Indicates that a person is identified by name as holding a specific role or position in a given context.
-
D.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
E.
loreRole
Indicates the specific narrative or canonical function an entity fulfills within a fictional or mythological lore.
- 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_69e0c47a95908190ae3e19b716accb3d |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fc2124c8190a79cf115a1d30283 |
completed | April 28, 2026, 8:59 p.m. |
| PD | Predicate disambiguation | batch_69e6be9a65888190a66598d62d20366c |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 7:06 p.m.