Triple
T2596033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tel HaShomer |
E58232
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Bnei Brak |
E102846
|
NE 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: Bnei Brak | Statement: [Tel HaShomer, near, Bnei Brak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bnei Brak Context triple: [Tel HaShomer, near, Bnei Brak]
-
A.
Bnei Brak
chosen
Bnei Brak is a densely populated city in Israel known as a major center of ultra-Orthodox Jewish life and culture.
-
B.
Herzliya
Herzliya is a coastal city in central Israel known as a high-tech and academic hub, home to major technology companies and institutions.
-
C.
Givatayim
Givatayim is a small, densely populated city in Israel’s Tel Aviv metropolitan area, known for its residential character and proximity to major urban centers.
-
D.
Holon
Holon is a city in central Israel, part of the Tel Aviv metropolitan area, known for its cultural institutions, museums, and diverse communities.
-
E.
Kiryat Ono
Kiryat Ono is a small suburban city in central Israel, located in the Tel Aviv metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd42978f881909f217e7ec9ac3144 |
completed | March 7, 2026, 7:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af83c798088190944e7d754aa9aa06 |
completed | March 10, 2026, 2:36 a.m. |
Created at: March 6, 2026, 9:49 p.m.