Triple
T32637578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katherine Hale |
E834389
|
entity |
| Predicate | countryOfSettingOfWorkAppearedIn |
P10686
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [Katherine Hale, countryOfSettingOfWorkAppearedIn, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfSettingOfWorkAppearedIn Context triple: [Katherine Hale, countryOfSettingOfWorkAppearedIn, United States]
-
A.
productionCountryOfWorkAppearsIn
Indicates that a country is the production country of a work in which a given entity appears.
-
B.
countryOfSetting
chosen
Indicates the country in which the setting or context of something (such as a story, event, or work) takes place.
-
C.
appearsInWorkCountryOfOrigin
Indicates that an entity appears in a work whose country of origin is the specified country.
-
D.
countryInWork
Indicates that a creative work is set in, associated with, or significantly involves a particular country.
-
E.
publisherCountryOfWork
Indicates the country where the publisher of a given work is based or operates.
- 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_69f3492dc2308190a88c6e30a3f3f576 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0067cde0f08190b2cd93af5f00d519 |
completed | May 10, 2026, 11:11 a.m. |
| PD | Predicate disambiguation | batch_6a0065820c8c8190994734433c64a30a |
completed | May 10, 2026, 11:01 a.m. |
Created at: May 1, 2026, 1:07 a.m.