Triple
T24825001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dogmatic Constitution on the Church |
E621162
|
entity |
| Predicate | numberOfParagraphs |
P69278
|
FINISHED |
| Object | 69 |
—
|
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: 69 | Statement: [Dogmatic Constitution on the Church, numberOfParagraphs, 69]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfParagraphs Context triple: [Dogmatic Constitution on the Church, numberOfParagraphs, 69]
-
A.
hasNumberOfParagraphs
chosen
Indicates that an entity is associated with a specific count of paragraphs it contains or comprises.
-
B.
numberOfPassages
Indicates the total count of distinct passages associated with or contained within a given entity or context.
-
C.
hasTwoParagraphs
Indicates that the related content or text is composed of exactly two distinct paragraphs.
-
D.
numberOfMainTexts
Indicates the quantity of primary or main textual components associated with an entity.
-
E.
hasParagraph
Indicates that one entity contains or is associated with a specific paragraph as part of its content or structure.
- 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_69e2fac0c3b881909110e5a56c6fa46f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f6430a93a48190854ce71df680b2fa |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 18, 2026, 5:05 a.m.