Triple
T26743160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deborah Morse |
E674320
|
entity |
| Predicate | jurisdictionOfEmployment |
P162357
|
FINISHED |
| Object | State of Alaska |
—
|
NE NERFINISHED |
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: State of Alaska | Statement: [Deborah Morse, jurisdictionOfEmployment, State of Alaska]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jurisdictionOfEmployment Context triple: [Deborah Morse, jurisdictionOfEmployment, State of Alaska]
-
A.
organizationJurisdiction
Indicates the legal or administrative area (such as a country, state, or city) within whose authority an organization operates or is governed.
-
B.
locationOfWork
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
C.
jurisdictionOfTraining
Indicates the legal or regulatory authority under which the training is conducted or recognized.
-
D.
placeOfOriginOfWork
Indicates the location where a work (such as an artwork, literary piece, or other creation) was originally produced or created.
-
E.
definedJurisdictionOf
Indicates that one entity formally establishes or specifies the scope, boundaries, or authority of another entity’s jurisdiction.
- 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_69eecda63a3881908095c47900692e65 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6250321088190ae3ed1dc9f2fcd03 |
completed | May 2, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69f623a7539c8190b71797f583da9f63 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f62473a38481909b919f88ffb5b492 |
completed | May 2, 2026, 4:21 p.m. |
Created at: April 27, 2026, 3:50 a.m.