Triple
T23877257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I: Exaudi orationem meam, Domine |
E592901
|
entity |
| Predicate | hasTextTheme |
P62774
|
FINISHED |
| Object | prayer for God’s hearing |
—
|
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: prayer for God’s hearing | Statement: [I: Exaudi orationem meam, Domine, hasTextTheme, prayer for God’s hearing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextTheme Context triple: [I: Exaudi orationem meam, Domine, hasTextTheme, prayer for God’s hearing]
-
A.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
B.
hasThemeType
chosen
Indicates that something is associated with or characterized by a particular thematic category or type.
-
C.
hasMaterialTheme
Indicates that something conceptually centers on, concerns, or thematically involves a particular material or substance.
-
D.
hasTextBy
Indicates that one entity (such as a document, work, or record) contains or is associated with text authored or written by another entity.
-
E.
hasTextFrom
Indicates that one entity contains, is derived from, or directly uses the textual content originating from 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_69e25d23a5c88190ae3999c70ca15e08 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cc02277c8190b0c15d6525f3b38d |
completed | April 29, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:15 p.m.