Triple
T33221425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trent Tucker Rule |
E850430
|
entity |
| Predicate | effectOnPlay |
P53074
|
FINISHED |
| Object | limits options to tip or direct tap with under 0.3 seconds |
—
|
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: limits options to tip or direct tap with under 0.3 seconds | Statement: [Trent Tucker Rule, effectOnPlay, limits options to tip or direct tap with under 0.3 seconds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnPlay Context triple: [Trent Tucker Rule, effectOnPlay, limits options to tip or direct tap with under 0.3 seconds]
-
A.
effectOnUsage
Indicates how one factor or condition changes the way something is used, including the extent, manner, or frequency of its usage.
-
B.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
C.
eventEffect
chosen
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
D.
capturesEffectOf
Indicates that one entity represents or records the impact, consequence, or outcome produced by another entity or process.
-
E.
effectOnOutput
Indicates how one factor, action, or condition influences or changes the resulting output of a process or system.
- 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_69f3496083dc8190b229bb6932dc548b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 1, 2026, 1:30 a.m.