Triple
T12912134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Power Armor |
E308887
|
entity |
| Predicate | providesEffect |
P106972
|
FINISHED |
| Object | increased damage resistance |
—
|
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: increased damage resistance | Statement: [Power Armor, providesEffect, increased damage resistance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providesEffect Context triple: [Power Armor, providesEffect, increased damage resistance]
-
A.
findsEffect
Indicates that one entity discovers, identifies, or determines the effect or outcome produced by another entity.
-
B.
ultimateEffect
Indicates the final or overall outcome that results from a preceding action, condition, or sequence of events.
-
C.
usesEffectType
Indicates that an entity employs or is associated with a particular type or category of effect in its operation or behavior.
-
D.
providesSensoryEffects
Indicates that one entity causes or contributes to sensory experiences or perceptions in another entity.
-
E.
specialEffectsBy
Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9719f96248190b746f9d4a468560c |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa9b7708190a9e9fa30f59ff580 |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9708a86bc8190bcdcf97e845bb413 |
completed | April 10, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:41 p.m.