Triple
T887438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suffering Servant |
E19161
|
entity |
| Predicate | primarySourceChapters |
P21432
|
FINISHED |
| Object | Isaiah 52 |
—
|
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: Isaiah 52 | Statement: [Suffering Servant, primarySourceChapters, Isaiah 52]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySourceChapters Context triple: [Suffering Servant, primarySourceChapters, Isaiah 52]
-
A.
primarySources
Indicates that one entity serves as an original, authoritative source of information or evidence for another entity.
-
B.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
C.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
D.
hasLocalChaptersIn
Indicates that an organization maintains one or more local chapters or branches within a specified geographic area or location.
-
E.
chapterNumber
Indicates the specific ordinal position a chapter occupies within a larger ordered work, such as a book or document.
- F. None of above. chosen
Provenance (4 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ae787bf081909533082ca013624a |
completed | March 1, 2026, 9:24 p.m. |
| PD | Predicate disambiguation | batch_69a4aa8ff8c48190a33b00acf65c1276 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ae774fac8190b3134d64086d65fe |
completed | March 1, 2026, 9:24 p.m. |
Created at: March 1, 2026, 7:39 p.m.