Triple
T11659880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deep Dark |
E277094
|
entity |
| Predicate | noiseLevelMechanic |
P32166
|
FINISHED |
| Object | vibration detection via sculk sensors |
—
|
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: vibration detection via sculk sensors | Statement: [Deep Dark, noiseLevelMechanic, vibration detection via sculk sensors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noiseLevelMechanic Context triple: [Deep Dark, noiseLevelMechanic, vibration detection via sculk sensors]
-
A.
noiseLevel
chosen
Indicates the intensity or amount of sound present in a given environment or from a specific source.
-
B.
noiseSource
Indicates that one entity is the origin or producer of a particular noise affecting another entity or the environment.
-
C.
noiseCompliance
Indicates that an entity adheres to specified rules or standards governing acceptable noise levels or sound emissions.
-
D.
soundMechanism
Indicates a relationship where one entity produces, transmits, or enables the production of sound for another entity or context.
-
E.
noisePolicy
Indicates the rules or constraints governing acceptable noise levels or noise-related behavior in a given context.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3d19c788190826d849a6ffedc72 |
completed | April 10, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69d88a73f9ac819095662042804bf40a |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:39 p.m.