Triple
T37664472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elder Guardian |
E937789
|
entity |
| Predicate | difficultyAffectsDamage |
P99960
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Elder Guardian, difficultyAffectsDamage, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: difficultyAffectsDamage Context triple: [Elder Guardian, difficultyAffectsDamage, Yes]
-
A.
damageAdjusted
Indicates that the amount of damage has been modified from its original value, typically to account for mitigating or amplifying factors.
-
B.
hasDifficultyEffect
Indicates that one entity causes a change in the difficulty level or challenge associated with another entity or activity.
-
C.
damageBonus
Indicates that an entity receives an additional amount of damage dealt beyond its base damage value.
-
D.
damageRating
Indicates the assessed level or severity of damage associated with an entity or event.
-
E.
damageScaling
chosen
Indicates how the amount of damage changes in proportion to certain factors, such as level, stats, or conditions.
- 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_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:18 p.m.