Triple
T26657384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camille Montes |
E666544
|
entity |
| Predicate | settingCountryOfStory |
P10686
|
FINISHED |
| Object | Bolivia |
—
|
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: Bolivia | Statement: [Camille Montes, settingCountryOfStory, Bolivia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingCountryOfStory Context triple: [Camille Montes, settingCountryOfStory, Bolivia]
-
A.
countryOfSetting
chosen
Indicates the country in which the setting or context of something (such as a story, event, or work) takes place.
-
B.
nationalityInStory
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
C.
nationalityOfFictionalSetting
Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
-
D.
countryOfFictionalContext
Indicates that a work of fiction is primarily set in, or contextually associated with, a particular country.
-
E.
storyWorld
Indicates the fictional universe or narrative setting within which a story, event, or character exists or takes place.
- 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_69ee9cf8c7188190b9b00270a8a89164 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:35 a.m.