Triple
T34113699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diane Siegler |
E874910
|
entity |
| Predicate | countryOfWorkSubject |
P146209
|
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: [Diane Siegler, countryOfWorkSubject, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfWorkSubject Context triple: [Diane Siegler, countryOfWorkSubject, United States]
-
A.
worksInCountry
Indicates that an entity performs its work or professional activities within the specified country.
-
B.
countryOfSubjectMatter
Indicates the country that the subject matter (e.g., a work, topic, or issue) primarily concerns or is associated with.
-
C.
workSubjectNationality
Indicates that the subject of a work has a specified nationality.
-
D.
countryInWork
Indicates that a creative work is set in, associated with, or significantly involves a particular country.
-
E.
workFromCountry
chosen
Indicates that an entity performs their work or job while being physically located in a specified country.
- 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_69f349a9271c81909576994c9ef7b179 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a01289f781481908f3788f8a719f2f4 |
completed | May 11, 2026, 12:53 a.m. |
| PD | Predicate disambiguation | batch_6a012823c7248190961e20be48dd6246 |
completed | May 11, 2026, 12:51 a.m. |
Created at: May 1, 2026, 1:53 a.m.