Triple
T11459329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Oro Province |
E271610
|
entity |
| Predicate | hasNumberOfCantons |
P87078
|
FINISHED |
| Object | more than 10 |
—
|
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: more than 10 | Statement: [El Oro Province, hasNumberOfCantons, more than 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfCantons Context triple: [El Oro Province, hasNumberOfCantons, more than 10]
-
A.
numberOfCantons
chosen
Indicates the total count of cantons associated with or contained within a given entity.
-
B.
foundingCantons
Indicates that the referenced entities are the original member regions or states that established or founded a larger political or organizational unit.
-
C.
governingCantonCapital
Indicates that a city serves as the capital and administrative seat of the specified canton.
-
D.
hasCanton
Indicates that an entity is administratively divided into, or associated with, a specific canton.
-
E.
hasNeighbouringCanton
Indicates that one canton is geographically adjacent to and shares a common border with another canton.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f2138081909408c7916cef99c9 |
completed | April 9, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69d80867ff248190bb157fa9e355353b |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.