Triple
T30581406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antarctic Vibranium |
E778390
|
entity |
| Predicate | effectOnMetals |
P180540
|
FINISHED |
| Object | liquefies other metals |
—
|
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: liquefies other metals | Statement: [Antarctic Vibranium, effectOnMetals, liquefies other metals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnMetals Context triple: [Antarctic Vibranium, effectOnMetals, liquefies other metals]
-
A.
associatedMetal
Indicates a relationship where one entity is linked or connected to a particular metal, such as by composition, usage, origin, or symbolic association.
-
B.
metalColor
Indicates the color attribute associated specifically with a metal or metallic material.
-
C.
effectOnSkin
Indicates the impact or influence that something has on the condition, appearance, or health of skin.
-
D.
typicalValueForMetals
Indicates the characteristic or commonly observed value of a given property specifically for metals.
-
E.
incorporatesMetalInfluence
Indicates that something includes or integrates stylistic, structural, or thematic elements characteristic of metal (e.g., metal music or metal aesthetics) into its overall composition or design.
- 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_69f224a04b248190b0ca443ec86207b8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: April 29, 2026, 8:23 p.m.