Triple
T19299778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaark farm |
E482661
|
entity |
| Predicate | countryInNarrative |
P10686
|
FINISHED |
| Object | colonial America |
—
|
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: colonial America | Statement: [Vaark farm, countryInNarrative, colonial America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryInNarrative Context triple: [Vaark farm, countryInNarrative, colonial America]
-
A.
nationalityInStory
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
B.
countryInReality
Indicates that a given country exists or is recognized as such within a particular real-world context or scenario.
-
C.
locatedInFictionalCountry
Indicates that an entity exists or is situated within a country that is fictional rather than real.
-
D.
countryOfSetting
chosen
Indicates the country in which the setting or context of something (such as a story, event, or work) takes place.
-
E.
coveredCountry
Indicates that one entity includes or provides coverage for the territory or jurisdiction of 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc895c68819096d06746f1b84e06 |
completed | April 20, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0bc7508190a6f9d56bd4c3404f |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:31 p.m.