Triple
T26667173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zande |
E672216
|
entity |
| Predicate | isSpokenInPrefecture |
P105510
|
FINISHED |
| Object |
Mbomou
Mbomou is a prefecture in the southeastern Central African Republic, bordering the Democratic Republic of the Congo and known for its diverse ethnic groups and forested landscapes.
|
E1734757
|
NE FINISHED |
How this triple was built (3 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: Mbomou | Statement: [Zande, isSpokenInPrefecture, Mbomou]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mbomou Triple: [Zande, isSpokenInPrefecture, Mbomou]
Generated description
Mbomou is a prefecture in the southeastern Central African Republic, bordering the Democratic Republic of the Congo and known for its diverse ethnic groups and forested landscapes.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSpokenInPrefecture Context triple: [Zande, isSpokenInPrefecture, Mbomou]
-
A.
spokenInPrefecture
chosen
Indicates that a particular language or dialect is spoken within the geographic area of a specified prefecture.
-
B.
isSpokenInAdministrativeUnit
Indicates that a particular language is used or officially spoken within a specified administrative unit or region.
-
C.
isPrefecture
Indicates that one entity functions as an administrative prefecture governing or representing the other entity.
-
D.
hasPrefecture
Indicates that one administrative region or country possesses or is associated with a specific prefecture as a subordinate territorial unit.
-
E.
locatedInRegionOfPrefecture
Indicates that one entity is geographically situated within a specific region that belongs to or is administered as part of a given prefecture.
- F. None of above.
Provenance (6 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_69eecda00a9c8190b2691f4d89db03b6 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a11ec4eb7e88190bafb81ed09480ea2 |
completed | May 23, 2026, 6:05 p.m. |
| NEDg | Description generation | batch_6a11ed11cca08190b0700be2359851d0 |
completed | May 23, 2026, 6:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a11edfed6288190b0c75e8c4a0216ba |
completed | May 23, 2026, 6:12 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 3:10 a.m.