Triple
T348662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reform Judaism |
E6993
|
entity |
| Predicate | hasViewOnZionism |
P11075
|
FINISHED |
| Object | generally supportive of the State of Israel |
—
|
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: generally supportive of the State of Israel | Statement: [Reform Judaism, hasViewOnZionism, generally supportive of the State of Israel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewOnZionism Context triple: [Reform Judaism, hasViewOnZionism, generally supportive of the State of Israel]
-
A.
hadViewOnReligion
Indicates that an entity held a particular perspective, belief, or stance regarding religion.
-
B.
viewsHalakhaAs
Indicates that one entity regards or interprets Halakha (Jewish law) in a particular way, such as considering it authoritative, binding, flexible, or symbolic.
-
C.
hasViewOnSociety
Indicates that an entity holds a particular perspective, opinion, or stance regarding society or social structures.
-
D.
hasSynagogueUnion
Indicates that there exists an organizational or formal union connecting one synagogue with another synagogue or group of synagogues.
-
E.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb1c1c908190b3a01de893207ed1 |
completed | Feb. 28, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69a2e955d1f88190bd687c46fa7c5469 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea60e590819081779a6510918d9b |
completed | Feb. 28, 2026, 1:15 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.