Triple
T37945039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | קו ירוק |
E946581
|
entity |
| Predicate | הפך לפחות ברור בשטח בעקבות |
P189648
|
FINISHED |
| Object | הקמת התנחלויות בגדה המערבית |
—
|
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: הקמת התנחלויות בגדה המערבית | Statement: [קו ירוק, הפך לפחות ברור בשטח בעקבות, הקמת התנחלויות בגדה המערבית]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: הפך לפחות ברור בשטח בעקבות Context triple: [קו ירוק, הפך לפחות ברור בשטח בעקבות, הקמת התנחלויות בגדה המערבית]
-
A.
isEasierToSeeThan
Indicates that one entity is more visually noticeable or discernible than another under comparable viewing conditions.
-
B.
followsMoreClosely
Indicates that one entity follows another with a smaller distance, delay, or deviation than some alternative or reference follower.
-
C.
שקיפות
Indicates that an entity or process is conducted in an open, clear, and visible manner, allowing others to access information and understand how decisions or actions are taken.
-
D.
observedMoreStrictlyIn
Indicates that one entity is monitored, regulated, or enforced with greater strictness or rigor in comparison to another context or entity.
-
E.
התמחות
Indicates a specialization or focused expertise that one entity has in a particular field, subject, or activity.
- 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_69f76ef531ac8190ae6d99e5786e76ec |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc7b78f9481909f4f8fc2e3fdcde1 |
completed | May 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69fbbd18c9908190928d274f8731dfa8 |
completed | May 6, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69fbc7b6c2c88190ad4f58980834053c |
completed | May 6, 2026, 10:59 p.m. |
Created at: May 3, 2026, 4:20 p.m.