Triple
T35833044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mel Blount rule |
E1035850
|
entity |
| Predicate | effectOnStrategy |
P190074
|
FINISHED |
| Object | encouraged more timing-based passing routes |
—
|
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: encouraged more timing-based passing routes | Statement: [Mel Blount rule, effectOnStrategy, encouraged more timing-based passing routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnStrategy Context triple: [Mel Blount rule, effectOnStrategy, encouraged more timing-based passing routes]
-
A.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
B.
effectOnUsage
Indicates how one factor or condition changes the way something is used, including the extent, manner, or frequency of its usage.
-
C.
effectOnFlags
Indicates how an action or event changes, sets, or influences the state of one or more flags.
-
D.
effectOnPath
chosen
Indicates the influence or change that one entity or action has on the course, route, or trajectory of another.
-
E.
effectOnOthers
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
- 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_69f76e192a94819082db360cb91e6a8d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
Created at: May 3, 2026, 4:06 p.m.