Triple
T24742829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laka |
E618612
|
entity |
| Predicate | spokenInNeighboringRegionsOf |
P157697
|
FINISHED |
| Object | Chad |
—
|
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: Chad | Statement: [Laka, spokenInNeighboringRegionsOf, Chad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenInNeighboringRegionsOf Context triple: [Laka, spokenInNeighboringRegionsOf, Chad]
-
A.
spokenInLocality
Indicates that a language, dialect, or speech form is used or spoken within a specific locality or geographic area.
-
B.
isSpokenOn
Indicates that a particular language, phrase, or utterance is used or occurs during a specified time, event, or occasion.
-
C.
isSpokenInAdministrativeUnit
Indicates that a particular language is used or officially spoken within a specified administrative unit or region.
-
D.
spokenInRuralAreasOf
Indicates that something (typically a language, dialect, or speech variety) is used or spoken primarily in the rural areas of a specified region or country.
-
E.
hasNearbyProvince
Indicates that one province is geographically close to or directly adjacent to another province.
- 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442a977b08190b44eac040cb90211 |
completed | May 1, 2026, 6:05 a.m. |
| PDg | Predicate description generation | batch_69f44a3adb7c8190941572f718b3b93c |
completed | May 1, 2026, 6:37 a.m. |
Created at: April 18, 2026, 4:18 a.m.