Triple
T10777210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aniocha South |
E254228
|
entity |
| Predicate | electoralWardCount |
P63824
|
FINISHED |
| Object | multiple wards |
—
|
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: multiple wards | Statement: [Aniocha South, electoralWardCount, multiple wards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electoralWardCount Context triple: [Aniocha South, electoralWardCount, multiple wards]
-
A.
numberOfWards
chosen
Indicates the quantitative relationship specifying how many wards are associated with a given entity.
-
B.
hasNumberOfCouncillors
Indicates the relationship that specifies how many councillors are associated with a given entity.
-
C.
electoralWardFor
Indicates that one entity serves as the electoral ward or voting district in which another entity (such as a place or address) is located or represented.
-
D.
numberOfAreaCouncils
Indicates the total count of area councils associated with a given entity.
-
E.
hasNumberOfConstituencies
Indicates the specific count of constituencies associated with an entity.
- 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_69d7329d8c908190bddad40685133ea1 |
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.