Triple
T211579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tridentine Mass |
E4730
|
entity |
| Predicate | rubricsEmphasize |
P3362
|
FINISHED |
| Object | silence |
—
|
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: silence | Statement: [Tridentine Mass, rubricsEmphasize, silence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rubricsEmphasize Context triple: [Tridentine Mass, rubricsEmphasize, silence]
-
A.
marks
Indicates that one entity makes a visible or symbolic sign on, or designates, another entity for identification, emphasis, or distinction.
-
B.
highlights
chosen
Indicates that one entity draws special attention to, emphasizes, or visually marks another entity as important or noteworthy.
-
C.
isHeavilyWeightedToward
Indicates that something is strongly biased or disproportionately oriented in favor of one side, option, or aspect over others.
-
D.
isImportantFor
Indicates that something holds significant value, relevance, or necessity in relation to something else.
-
E.
awardCriteria
Indicates the standards or conditions used to determine eligibility for receiving an award or recognition.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b4f71b88190866c8262922ae204 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.