Triple
T37662546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potion of Weakness |
E937747
|
entity |
| Predicate | attackDamageModifier |
P66042
|
FINISHED |
| Object | -4 attack damage (Java Edition, default) |
—
|
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: -4 attack damage (Java Edition, default) | Statement: [Potion of Weakness, attackDamageModifier, -4 attack damage (Java Edition, default)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attackDamageModifier Context triple: [Potion of Weakness, attackDamageModifier, -4 attack damage (Java Edition, default)]
-
A.
attackValue
Indicates the offensive strength or damage potential an entity can inflict in an interaction or combat scenario.
-
B.
damageBonus
Indicates that an entity receives an additional amount of damage dealt beyond its base damage value.
-
C.
attackEffect
Indicates that one entity’s attack produces a specific effect or consequence on another entity.
-
D.
damageAdjusted
chosen
Indicates that the amount of damage has been modified from its original value, typically to account for mitigating or amplifying factors.
-
E.
attackHealthRatio
Indicates the proportion between an entity’s current health and its maximum health at the moment of an attack.
- 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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fce7671f108190bf3ebf54339068b5 |
completed | May 7, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69fce5b5a84c81908ac1b5b9f08d48d0 |
completed | May 7, 2026, 7:19 p.m. |
Created at: May 3, 2026, 4:18 p.m.