Triple
T11463819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thinline |
E271726
|
entity |
| Predicate | hasPageContent |
P90926
|
FINISHED |
| Object | complete biblical text |
—
|
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: complete biblical text | Statement: [Thinline, hasPageContent, complete biblical text]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPageContent Context triple: [Thinline, hasPageContent, complete biblical text]
-
A.
hasPage
Indicates that one entity includes, is associated with, or is documented by a specific page (such as a web page or document page).
-
B.
hasContentFrom
Indicates that one entity’s content is derived from, includes, or is based on another entity.
-
C.
hasCollectionContent
chosen
Indicates that a collection includes or contains a specific item, element, or content as part of it.
-
D.
hasContentSummary
Indicates that an entity is associated with a brief descriptive summary of its content.
-
E.
hasPageCountApprox
Indicates that an entity is associated with an approximate or estimated number of pages, rather than an exact page count.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f488248190b9f603cd31c72174 |
completed | April 9, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69d80867ff248190bb157fa9e355353b |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.