Triple
T37457701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shadowreaper Anduin |
E930839
|
entity |
| Predicate | damageTypeFocus |
P139151
|
FINISHED |
| Object | Direct damage |
—
|
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: Direct damage | Statement: [Shadowreaper Anduin, damageTypeFocus, Direct damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damageTypeFocus Context triple: [Shadowreaper Anduin, damageTypeFocus, Direct damage]
-
A.
damageClass
chosen
Indicates the type or category of damage associated with an action, event, or interaction between entities.
-
B.
damageBasis
Indicates the underlying reason, cause, or basis on which damage is determined or assessed in a given context.
-
C.
damageEffect
Indicates that one entity causes harm, reduction, or deterioration to another entity or its properties.
-
D.
damageRating
Indicates the assessed level or severity of damage associated with an entity or event.
-
E.
damageScope
Indicates the extent or range of harm or impairment caused by an event, action, or condition.
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaebc8f2c8190b94f1b4a3ec92e8c |
completed | May 6, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:17 p.m.