Triple
T798536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Region |
E17075
|
entity |
| Predicate | siblingRegion |
P363
|
FINISHED |
| Object | West Region |
—
|
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: West Region | Statement: [East Region, siblingRegion, West Region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: siblingRegion Context triple: [East Region, siblingRegion, West Region]
-
A.
neighboringRegion
Indicates that two regions share a common boundary or are directly adjacent to each other geographically.
-
B.
sibling
chosen
Indicates that two entities share at least one parent, making them brothers or sisters to each other.
-
C.
hasSisterProvince
Indicates that two provinces are related to each other as sister provinces, typically through a formal partnership or cooperative relationship.
-
D.
borderRegionOf
Indicates that one region lies along, touches, or forms part of the boundary of another region.
-
E.
sisterGroup
Indicates that two groups share an immediate common ancestor in a hierarchy or classification, making them each other’s closest related group.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7b4d9548190aad5fdf1211cf8cd |
completed | March 1, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69a4a5122a008190b0c621b7bc588d41 |
completed | March 1, 2026, 8:44 p.m. |
Created at: March 1, 2026, 7:38 p.m.