Triple
T5402165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prove Thyself |
E120801
|
entity |
| Predicate | tierEffect |
P63773
|
FINISHED |
| Object | Higher tiers increase the cooperative action speed bonus |
—
|
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: Higher tiers increase the cooperative action speed bonus | Statement: [Prove Thyself, tierEffect, Higher tiers increase the cooperative action speed bonus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tierEffect Context triple: [Prove Thyself, tierEffect, Higher tiers increase the cooperative action speed bonus]
-
A.
notableEffect
Indicates that one entity has a significant impact, consequence, or influence on another entity or situation.
-
B.
primaryEffect
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
C.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
D.
foodEffect
Indicates how consuming a particular food influences or changes another entity, such as an organism, condition, or process.
-
E.
perkType
Indicates the specific category or kind of benefit, bonus, or advantage associated with an entity or situation.
- 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_69bd46391c0c81909fa484446732b6a3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8932b8bc8190bd31e11b167a7212 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd84660ea08190a641084814fcf94d |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8931302c81908afcb0f011e91f09 |
completed | March 20, 2026, 5:51 p.m. |
Created at: March 20, 2026, 2:04 p.m.