Triple
T4528574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union conference |
E106239
|
entity |
| Predicate | subdividesInto |
P747
|
FINISHED |
| Object | local conferences |
—
|
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: local conferences | Statement: [Union conference, subdividesInto, local conferences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subdividesInto Context triple: [Union conference, subdividesInto, local conferences]
-
A.
subdividedBy
Indicates that something is divided into smaller parts or sections by another entity or criterion.
-
B.
hasSubdivision
chosen
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
C.
hasTypeOfSubdivision
Indicates that one administrative or territorial unit is classified as a specific kind or category of subdivision.
-
D.
parallelSubdivision
Indicates that one structure or process is divided into multiple parts that proceed or are handled simultaneously alongside each other.
-
E.
hasSubdivisionExample
Indicates that one entity is an example or instance of a subdivision or component part of another 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_69bd43f3d6e08190a91824f833d51bbe |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd5779593081908593537b9239e01b |
completed | March 20, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69bd521cf77c819083852de3094d1377 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:03 p.m.