Triple
T37460568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mad Scientist |
E930905
|
entity |
| Predicate | effectCategory |
P195919
|
FINISHED |
| Object | Deck thinning |
—
|
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: Deck thinning | Statement: [Mad Scientist, effectCategory, Deck thinning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectCategory Context triple: [Mad Scientist, effectCategory, Deck thinning]
-
A.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
B.
effectOnUsage
Indicates how one factor or condition changes the way something is used, including the extent, manner, or frequency of its usage.
-
C.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
D.
capturesEffectOf
Indicates that one entity represents or records the impact, consequence, or outcome produced by another entity or process.
-
E.
ultimateEffect
Indicates the final or overall outcome that results from a preceding action, condition, or sequence of events.
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fdee770af48190aca2670db50f8b49 |
completed | May 8, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69fdecec98a08190a357d816dc2a6dbe |
completed | May 8, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69fdee75d1408190bba58a9cef200a54 |
completed | May 8, 2026, 2:08 p.m. |
Created at: May 3, 2026, 4:17 p.m.