Triple
T34376759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yetûr |
E882305
|
entity |
| Predicate | hasSourceTextTradition |
P183720
|
FINISHED |
| Object | Masoretic Text |
—
|
NE NERFINISHED |
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: Masoretic Text | Statement: [Yetûr, hasSourceTextTradition, Masoretic Text]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSourceTextTradition Context triple: [Yetûr, hasSourceTextTradition, Masoretic Text]
-
A.
hasSourceTradition
Indicates that something originates from, or is derived within, a particular cultural, religious, intellectual, or historical tradition.
-
B.
hasTraditionalTranslation
Indicates that one entity serves as the established or customary translation of another entity in a traditional or historically accepted sense.
-
C.
hasScriptTradition
Indicates that one entity follows, preserves, or is associated with a particular script or writing tradition used for representation or transmission.
-
D.
hasTraditionalInterpretation
Indicates that something is associated with or understood according to a long-established or customary interpretation.
-
E.
hasTextualTransmission
chosen
Indicates that a work, idea, or content has been passed down, preserved, or conveyed through written or textual forms over time.
- 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_69f349bf5d7481908dd5da4cbdf74047 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd474b7e788190a9bb9b542d878f60 |
completed | May 8, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69fd46d8b2f0819099d92d72c902f60e |
completed | May 8, 2026, 2:13 a.m. |
Created at: May 1, 2026, 1:59 a.m.