Triple
T3155271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inner Light |
E65970
|
entity |
| Predicate | usedInPractice |
P46656
|
FINISHED |
| Object | silent worship |
—
|
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: silent worship | Statement: [Inner Light, usedInPractice, silent worship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInPractice Context triple: [Inner Light, usedInPractice, silent worship]
-
A.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
B.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
C.
usedInIndustry
Indicates that something is employed or applied within a particular industry or industrial sector.
-
D.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
E.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
- 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_69ad8584485081909ed529e890cadc4a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5e97548819084643586fff2e3cb |
completed | March 8, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9dfbf0348190952a6bca8fc5fed1 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada1e4f7288190a80a1672e458132d |
completed | March 8, 2026, 4:20 p.m. |
Created at: March 8, 2026, 3:05 p.m.