Triple
T1901570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zadok the Priest |
E37699
|
entity |
| Predicate | textIncipit |
P9883
|
FINISHED |
| Object | Zadok the priest and Nathan the prophet anointed Solomon king |
—
|
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: Zadok the priest and Nathan the prophet anointed Solomon king | Statement: [Zadok the Priest, textIncipit, Zadok the priest and Nathan the prophet anointed Solomon king]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textIncipit Context triple: [Zadok the Priest, textIncipit, Zadok the priest and Nathan the prophet anointed Solomon king]
-
A.
readPoemAt
Indicates that an entity reads or performs a poem at a specific time, place, or event.
-
B.
textOpeningTranslation
Indicates that a text serves as a translation of the opening section of another text.
-
C.
textFragment
chosen
Indicates that one piece of text is a constituent part or segment of a larger text.
-
D.
literaryUnit
Indicates that one entity is a distinct segment or component (such as a chapter, scene, or passage) within a larger literary work or text.
-
E.
scriptOfInscription
Indicates the writing system or script in which a given inscription is written.
- 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_69a8861be7148190a680937ec451a304 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafe9f8b0819086d8f6288511c66d |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.