Triple
T25351452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hildred Geertz |
E635696
|
entity |
| Predicate | primaryFieldworkCountry |
P64661
|
FINISHED |
| Object | Indonesia |
—
|
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: Indonesia | Statement: [Hildred Geertz, primaryFieldworkCountry, Indonesia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryFieldworkCountry Context triple: [Hildred Geertz, primaryFieldworkCountry, Indonesia]
-
A.
primaryLocationCountry
Indicates the country that serves as the main or primary location associated with the subject.
-
B.
countryOfResearch
chosen
Indicates the country where the research activity was primarily conducted or based.
-
C.
countryOfMainInvestigation
Indicates the country in which the primary or main part of an investigation is conducted or focused.
-
D.
mainCountry
Indicates that one country is the primary or most significant country associated with a given entity or context.
-
E.
workFromCountry
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_69e75a9ac5d881909387ed766e20cd47 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: April 21, 2026, 1:34 p.m.