Triple
T9477232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shell Toss |
E228545
|
entity |
| Predicate | damageBasis |
P88334
|
FINISHED |
| Object | Koops’s attack power |
—
|
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: Koops’s attack power | Statement: [Shell Toss, damageBasis, Koops’s attack power]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damageBasis Context triple: [Shell Toss, damageBasis, Koops’s attack power]
-
A.
damageLeadsTo
Indicates that one instance of damage causally results in or contributes to another specified outcome or condition.
-
B.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
-
C.
damageDescription
Indicates a textual description of the nature, extent, or characteristics of damage associated with an entity or event.
-
D.
damageAdjusted
Indicates that the amount of damage has been modified from its original value, typically to account for mitigating or amplifying factors.
-
E.
damageAssociatedWith
Indicates a relationship where one entity is linked to causing, contributing to, or being responsible for damage affecting another entity.
- 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_69ca847162c48190b079076c9595513c |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd801386948190890133f622ff360b |
completed | April 1, 2026, 8:29 p.m. |
| PD | Predicate disambiguation | batch_69cca55f01b081908dc0f12eaa45f832 |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69cca89d0f0c8190b4528990fe708fca |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:54 p.m.