Triple
T11829752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tucupita |
E281354
|
entity |
| Predicate | hasLanguageInCommonWith |
P33593
|
FINISHED |
| Object | rest of Venezuela |
—
|
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: rest of Venezuela | Statement: [Tucupita, hasLanguageInCommonWith, rest of Venezuela]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageInCommonWith Context triple: [Tucupita, hasLanguageInCommonWith, rest of Venezuela]
-
A.
sharesLanguageWith
chosen
Indicates that two entities use at least one common language for communication.
-
B.
hasCommonLoanwordsFrom
Indicates that two languages share loanwords that originate from the same source language.
-
C.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
D.
sharesLinguisticFamilyWith
Indicates that two languages belong to the same linguistic family or branch within a language family.
-
E.
isLinguaFrancaOf
Indicates that a language serves as a common medium of communication between speakers of different native languages within a particular region, community, or context.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62b75dc8190b27d24e46a262a11 |
completed | April 10, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69d8a251fc08819095933f1d13c3b742 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.