Triple
T30581419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antarctic Vibranium |
E778390
|
entity |
| Predicate | existsInRealWorld |
P29186
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Antarctic Vibranium, existsInRealWorld, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: existsInRealWorld Context triple: [Antarctic Vibranium, existsInRealWorld, no]
-
A.
soldInRealWorld
Indicates that the item or product is actually sold or available for purchase in the physical, real-world marketplace.
-
B.
realWorldInstanceOf
Indicates that an entity is a concrete, real-world example or occurrence of a more abstract type, concept, or class.
-
C.
hasRealWorldOrigin
Indicates that something is derived from, based on, or directly connected to an actual entity, event, or source in the real world.
-
D.
realityStatus
chosen
Indicates the relationship between an entity and its state of existence or authenticity within a given context or world (e.g., real, fictional, hypothetical, simulated).
-
E.
hasRealityCounterpartInFiction
Indicates that a fictional element corresponds to or is based on a real-world counterpart within a work of fiction.
- 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_69f224a04b248190b0ca443ec86207b8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6894261048190aa19ffe41a34413c |
completed | May 2, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:23 p.m.