Triple
T26567911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Encratism |
E666740
|
entity |
| Predicate | textualSourceMentionedBy |
P134241
|
FINISHED |
| Object | Eusebius of Caesarea |
—
|
NE NERFINISHED |
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: Eusebius of Caesarea | Statement: [Encratism, textualSourceMentionedBy, Eusebius of Caesarea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textualSourceMentionedBy Context triple: [Encratism, textualSourceMentionedBy, Eusebius of Caesarea]
-
A.
literarySource
Indicates that one entity serves as the written or literary origin, reference, or basis for another entity.
-
B.
locatedInTextualSource
chosen
Indicates that information about an entity or relation appears within, or is documented by, a specific textual source.
-
C.
eraMentioned
Indicates that a specific historical or temporal era is explicitly referenced or mentioned in a given context.
-
D.
textSources
Indicates that one entity serves as a source or origin for the text content associated with another entity.
-
E.
mentionedWith
Indicates that two entities are mentioned together or in close association within the same context, such as a document, sentence, or conversation.
- 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_69ee9cfa21c081909e4e36e087debfc6 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f614a0c2408190b494a3d1f624c042 |
completed | May 2, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69f602d7b1b0819095ddd3b5169f8ce2 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 27, 2026, 1:56 a.m.