Triple
T10775856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wadai |
E254194
|
entity |
| Predicate | ethnolinguisticZone |
P90751
|
FINISHED |
| Object | Saharan |
—
|
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: Saharan | Statement: [Wadai, ethnolinguisticZone, Saharan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethnolinguisticZone Context triple: [Wadai, ethnolinguisticZone, Saharan]
-
A.
ethnoLinguisticRegionOf
Indicates that a region is defined or characterized by the shared ethnic and linguistic identity of the group associated with it.
-
B.
ethnolinguisticCluster
chosen
Indicates a relationship where entities are grouped together based on shared ethnic and linguistic characteristics, treating them as part of the same ethnolinguistic cluster.
-
C.
ethnolinguisticGroups
Indicates a relationship where groups are categorized or associated based on shared ethnic and linguistic characteristics.
-
D.
linguisticArea
Indicates a regional context in which languages share features due to geographic proximity and contact rather than common genetic origin.
-
E.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7329cc6c881908f827edff941d456 |
completed | April 9, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69d6f31455648190b5c24690487b1b54 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:16 p.m.