Triple
T4943989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hades’s helm of invisibility |
E111001
|
entity |
| Predicate | perceptionEffect |
P35696
|
FINISHED |
| Object | prevents others from seeing the wearer |
—
|
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: prevents others from seeing the wearer | Statement: [Hades’s helm of invisibility, perceptionEffect, prevents others from seeing the wearer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perceptionEffect Context triple: [Hades’s helm of invisibility, perceptionEffect, prevents others from seeing the wearer]
-
A.
influencedPerceptionOf
Indicates that one entity has affected, shaped, or altered how another entity is perceived or understood.
-
B.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
C.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
D.
hasPerception
Indicates that one entity is aware of, senses, or recognizes another entity or phenomenon.
-
E.
providesSensoryEffects
chosen
Indicates that one entity causes or contributes to sensory experiences or perceptions in another entity.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70a7650c8190b046b65072fd8eae |
completed | March 20, 2026, 4:07 p.m. |
| PD | Predicate disambiguation | batch_69bd6c389b9881908ad7fb1c5393c1b1 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.