Triple
T6666439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeffrey Maier interference play |
E151614
|
entity |
| Predicate | ruleIssue |
P72339
|
FINISHED |
| Object | spectator interference |
—
|
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: spectator interference | Statement: [Jeffrey Maier interference play, ruleIssue, spectator interference]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ruleIssue Context triple: [Jeffrey Maier interference play, ruleIssue, spectator interference]
-
A.
raisesIssue
Indicates that one entity brings up, reports, or formally submits a concern, problem, or topic for attention to another entity or system.
-
B.
ruleNumber
Indicates that an entity is associated with a specific rule identified by its number within a set of rules.
-
C.
languagePolicyIssue
Indicates that there is a problem, conflict, or concern related to rules or practices governing language use.
-
D.
possibleIssue
Indicates that there is a potential or suspected problem, defect, or undesired condition associated with the referenced entity or situation, though it is not yet confirmed.
-
E.
knownIssue
Indicates that the subject has an issue or problem that is already identified, recognized, or documented.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce738fe88190a5557900efeec7ec |
completed | March 27, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69c6ad09974c81908784300ae218961f |
completed | March 27, 2026, 4:15 p.m. |
| PDg | Predicate description generation | batch_69c6ce72809c8190be85f6e42ca1c8ea |
completed | March 27, 2026, 6:37 p.m. |
Created at: March 27, 2026, 2:02 p.m.