Triple
T13379372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | משמר הגבול |
E319273
|
entity |
| Predicate | מדים |
P96191
|
FINISHED |
| Object | מדים ירוקים |
—
|
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: מדים ירוקים | Statement: [משמר הגבול, מדים, מדים ירוקים]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: מדים Context triple: [משמר הגבול, מדים, מדים ירוקים]
-
A.
כולל
chosen
Indicates that something contains, includes, or encompasses something else as a part or subset.
-
B.
זמנם
Indicates a relationship involving the time allotted to, belonging to, or associated with certain entities (e.g., “their time”).
-
C.
हवामान
Indicates a relationship involving weather conditions or atmospheric state affecting entities or events.
-
D.
dimensions_km
Indicates the physical size or extent of something measured in kilometers, typically specifying one or more linear dimensions (e.g., length, width, height).
-
E.
measureOf
Indicates that one entity serves as a quantitative or qualitative assessment or metric describing a property, extent, or magnitude of another entity.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce56c6c8190adf4e19f6d1bc233 |
completed | April 11, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69d9a03189908190a784a2755f8d81e1 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:33 p.m.