Triple
T2220882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zechariah |
E48136
|
entity |
| Predicate | visionTheme |
P25955
|
FINISHED |
| Object | restoration of Zion |
—
|
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: restoration of Zion | Statement: [Zechariah, visionTheme, restoration of Zion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visionTheme Context triple: [Zechariah, visionTheme, restoration of Zion]
-
A.
visionOf
Indicates that one entity is a visual representation, image, or depiction of another entity.
-
B.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
C.
themeFor
chosen
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
D.
containsVisionOf
Indicates that one entity includes, depicts, or embodies a visual representation or image of another entity.
-
E.
themeExamples
Indicates that the related entity serves as an example or illustration of the theme expressed by the subject.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0156c8c819083e3e3b6ede1e951 |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdac31d8819092d17815e11921e9 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.