Triple
T28716044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agadez Region |
E729962
|
entity |
| Predicate | areaRankingInNiger |
P49074
|
FINISHED |
| Object | largest region by area |
—
|
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: largest region by area | Statement: [Agadez Region, areaRankingInNiger, largest region by area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaRankingInNiger Context triple: [Agadez Region, areaRankingInNiger, largest region by area]
-
A.
hasAreaRankInNigeria
chosen
Indicates that one entity holds a specific rank in terms of area size within the context of Nigeria.
-
B.
areaRankingInAfrica
Indicates the relative position of an entity in a size-based ranking of areas within Africa.
-
C.
areaRankingInCameroon
Indicates the relative position of an entity in a ranked list based on its area size within Cameroon.
-
D.
areaRankingInChad
Indicates the relative position of an entity in a size-based ranking specifically within the geographic context of Chad.
-
E.
majorStatesInNigeria
Indicates that the subject is one of the principal or most significant states within the country of Nigeria.
- 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_69f043e7d5a4819094b18aca10b1e024 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f656db9bd88190b7e5da4c0da9a479 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 5:50 a.m.