Triple
T1715443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World TeamTennis |
E37278
|
entity |
| Predicate | matchStructure |
P32270
|
FINISHED |
| Object | multiple sets across different 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: multiple sets across different events | Statement: [World TeamTennis, matchStructure, multiple sets across different events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchStructure Context triple: [World TeamTennis, matchStructure, multiple sets across different events]
-
A.
matchType
Indicates the specific category or nature of how two or more entities correspond or align with each other within a given context.
-
B.
supportsStructure
Indicates that one entity bears or provides physical support to another entity, helping to hold it up or maintain its structural stability.
-
C.
segmentStructure
Indicates that one entity represents a structural or organizational subdivision (a segment) within the overall structure of another entity.
-
D.
matches
Indicates that two entities correspond to or are in agreement with each other according to some defined criteria or pattern.
-
E.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab7521878c8190b9e7739b8c3fc705 |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61bd46d48190915500d75a9d8e94 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab752034348190a1cc20955ed24f6f |
completed | March 7, 2026, 12:45 a.m. |
Created at: March 4, 2026, 7:30 p.m.