Triple
T35758984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hardal yeshivot |
E1033520
|
entity |
| Predicate | viewOnArmyService |
P57126
|
FINISHED |
| Object | generally supportive of IDF service |
—
|
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 IDF service | Statement: [Hardal yeshivot, viewOnArmyService, generally supportive of IDF service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewOnArmyService Context triple: [Hardal yeshivot, viewOnArmyService, generally supportive of IDF service]
-
A.
viewOnMilitaryService
chosen
Indicates a stance or opinion that an entity holds regarding military service, such as its value, necessity, or acceptability.
-
B.
viewsMilitaryAs
Indicates that one entity holds a particular perception, attitude, or evaluative stance toward the military as an institution or concept.
-
C.
servedArmy
Indicates that an entity has performed military service in, or been a member of, a particular army.
-
D.
personReferredToMilitaryService
Indicates that one person has directed, recommended, or assigned another person to perform military service.
-
E.
stanceOnMilitaryService
Indicates an entity’s expressed position, attitude, or policy regarding military service.
- 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_69f76e1262f48190a313318665acc189 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd05ba6b2c81909c62b46237d10365 |
completed | May 7, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69fd03039e48819082b6e12c5453885a |
completed | May 7, 2026, 9:24 p.m. |
Created at: May 3, 2026, 4:06 p.m.