Triple
T8317568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WTA 1000 tournaments |
E194743
|
entity |
| Predicate | categorySubdivision |
P81901
|
FINISHED |
| Object | mandatory events |
—
|
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: mandatory events | Statement: [WTA 1000 tournaments, categorySubdivision, mandatory events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: categorySubdivision Context triple: [WTA 1000 tournaments, categorySubdivision, mandatory events]
-
A.
primarySubdivisionOf
Indicates that one administrative or territorial unit is the main first-level subdivision within a larger political or geographic entity.
-
B.
countrySubdivisionType
Indicates the specific type or category of an administrative or territorial subdivision within a country (e.g., state, province, region).
-
C.
countrySubdivision
Indicates that one geopolitical region is an administrative or territorial subdivision of a larger country.
-
D.
hasSubdivision
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
E.
subdividedBy
Indicates that something is divided into smaller parts or sections by another entity or criterion.
- F. None of above. chosen
Provenance (4 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_69ca82e6e2648190a31eaf6f4f757b2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f630ea881909fb639383e60aee9 |
completed | March 31, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69cb70bf689c8190a9d9b6b872abf53d |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb77690720819099de1e22b84a9563 |
completed | March 31, 2026, 7:27 a.m. |
Created at: March 30, 2026, 5:55 p.m.