Triple
T16868891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1 Corinthians 10 |
E410115
|
entity |
| Predicate | hasApproximateVerseCount |
P7673
|
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: [1 Corinthians 10, hasApproximateVerseCount, 33]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateVerseCount Context triple: [1 Corinthians 10, hasApproximateVerseCount, 33]
-
A.
approximateNumberOfVerses
chosen
Indicates an estimated or approximate count of verses associated with an entity.
-
B.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
-
C.
hasVersesBy
Indicates a relationship where a work, such as a song or poem, contains verses authored or written by a specific creator.
-
D.
hasVersesIn
Indicates that one entity (typically a text, chapter, or section) contains or is composed of verses found within another entity (such as a book, collection, or scripture).
-
E.
containsVerse
Indicates that one entity (typically a text or collection) includes a specific verse as part of its content.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b50a82348190b3e33fd558aa3c7f |
completed | April 18, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69e32b8cbb048190878a259cc5be960e |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.