Triple
T35637150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Junior WRC |
E1029751
|
entity |
| Predicate | relationshipToWRC |
P207081
|
FINISHED |
| Object | support championship |
—
|
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: support championship | Statement: [Junior WRC, relationshipToWRC, support championship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToWRC Context triple: [Junior WRC, relationshipToWRC, support championship]
-
A.
relationToWSBK
Indicates a specified type of relationship or association that an entity has with WSBK.
-
B.
relationToNASCAR
Indicates a relationship in which an entity is connected or relevant to NASCAR, such as through participation, affiliation, influence, or subject matter.
-
C.
relationToWTAFinals
Indicates how an entity is connected or related to the WTA Finals event (e.g., by participation, qualification, or outcome).
-
D.
relationToWinner
Indicates the specific relationship or connection an entity has to the winner of a contest, competition, or event.
-
E.
relationToATPTour
Indicates a relationship specifying how an entity is connected or related to the ATP Tour, such as participation in, affiliation with, or relevance to that professional tennis circuit.
- 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_69f76e087bdc8190a4794bf9c0bd7634 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a04d8348190a4819666eab42c9b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:05 p.m.