Triple
T7498030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verse of Purification |
E177182
|
entity |
| Predicate | hasVerseNumber |
P18696
|
FINISHED |
| Object | 33 |
—
|
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: 33 | Statement: [Verse of Purification, hasVerseNumber, 33]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVerseNumber Context triple: [Verse of Purification, hasVerseNumber, 33]
-
A.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
-
B.
containsVerse
Indicates that one entity (typically a text or collection) includes a specific verse as part of its content.
-
C.
hasVerseRange
Indicates a relationship where a text or passage is associated with a specific contiguous range of verses it spans.
-
D.
hasVersesBy
Indicates a relationship where a work, such as a song or poem, contains verses authored or written by a specific creator.
-
E.
verseNumber
chosen
Indicates the specific numbered position of a verse within an ordered sequence, such as in a chapter, song, or poem.
- 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_69c69f2696688190915a8458f2398211 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81b431481908214b69c6c8d83bc |
completed | March 27, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d266d88190982cf5d2ee2e9564 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:44 p.m.