Triple
T25384985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloodpack enforcer |
E631496
|
entity |
| Predicate | offensiveCapability |
P111358
|
FINISHED |
| Object | close-range 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: close-range damage | Statement: [Bloodpack enforcer, offensiveCapability, close-range damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offensiveCapability Context triple: [Bloodpack enforcer, offensiveCapability, close-range damage]
-
A.
defensiveCapability
Indicates the ability or capacity of an entity to protect itself or others against threats, attacks, or harm.
-
B.
warfareCapability
Indicates the ability or capacity of an entity to engage in, conduct, or support acts of warfare.
-
C.
offensiveForce
Indicates the use or application of aggressive or attacking power or violence by one entity against another.
-
D.
weaponCapability
Indicates that one entity has the ability to use, deploy, or function as a weapon against another entity or target.
-
E.
offensiveStrength
chosen
Indicates the degree or capacity of an entity to carry out effective attacks or aggressive actions against an opponent.
- 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_69e75a8c50788190aabaa9f96710fc43 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f5656795248190a732c8596a0e740d |
completed | May 2, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 1:46 p.m.