Triple
T20194445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volt Tackle |
E493045
|
entity |
| Predicate | hasSecondaryEffect |
P139138
|
FINISHED |
| Object | user takes recoil damage |
—
|
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: user takes recoil damage | Statement: [Volt Tackle, hasSecondaryEffect, user takes recoil damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondaryEffect Context triple: [Volt Tackle, hasSecondaryEffect, user takes recoil damage]
-
A.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
B.
hasSecondary
Indicates that an entity is associated with an additional or subordinate counterpart beyond its primary one.
-
C.
hasDirectEffect
Indicates that one entity produces an immediate and unmediated impact or change on another entity.
-
D.
hasSecondaryForces
Indicates that an entity is subject to or associated with additional, indirect, or supporting forces beyond its primary forces.
-
E.
hasSecondaryUsage
Indicates that an entity is associated with an additional, non-primary function or purpose beyond its main intended use.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad7ed548190a893110fa2ffb144 |
completed | April 20, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e55b11124c8190babacf2a0fe2d057 |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56700b1a08190ace53cf95827d72d |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:37 p.m.