Triple
T33342358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teke-Eboo languages |
E853704
|
entity |
| Predicate | secondaryCountryOfUse |
P198244
|
FINISHED |
| Object | Gabon |
—
|
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: Gabon | Statement: [Teke-Eboo languages, secondaryCountryOfUse, Gabon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryCountryOfUse Context triple: [Teke-Eboo languages, secondaryCountryOfUse, Gabon]
-
A.
primaryUseCountry
Indicates the country in which something is primarily used or most commonly utilized.
-
B.
usedForCountry
Indicates that something is used for, or serves a purpose related to, a specific country.
-
C.
laterPrimaryCountry
Indicates that one country becomes the primary or dominant country in a given context at a later time than another.
-
D.
countryOrRegionUsed
Indicates that something is used within, or applies to, a specific country or geographic region.
-
E.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
- F. None of above. chosen
Provenance (4 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fed48d8e148190a99c0aea29f8a3ee |
completed | May 9, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fed3c82a24819095e614e31ac0307f |
completed | May 9, 2026, 6:27 a.m. |
| PDg | Predicate description generation | batch_69fed48c92ec8190b3be88880d86de86 |
completed | May 9, 2026, 6:30 a.m. |
Created at: May 1, 2026, 1:34 a.m.