Triple
T12787737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bron |
E305674
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Kiryat Ono |
E158565
|
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: Kiryat Ono | Statement: [Bron, twinTown, Kiryat Ono]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiryat Ono Context triple: [Bron, twinTown, Kiryat Ono]
-
A.
Kiryat Ono
chosen
Kiryat Ono is a small suburban city in central Israel, located in the Tel Aviv metropolitan area.
-
B.
Kiryat Haim
Kiryat Haim is a coastal neighborhood in the northern Israeli city of Haifa, known for its beachfront, residential character, and proximity to the Haifa Bay industrial and port areas.
-
C.
Kiryat Shmona
Kiryat Shmona is a northern Israeli city near the Lebanese border, known for its strategic location and frequent exposure to cross-border conflict.
-
D.
Kiryat Gat
Kiryat Gat is a city in south-central Israel known for its industrial zones, high-tech facilities, and location between the coastal plain and the Negev desert.
-
E.
Kfar Saba
Kfar Saba is a city in central Israel, known as a suburban and commercial hub in the Sharon plain near Tel Aviv.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e5dbdb88190a1b06721ada51627 |
completed | April 10, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3cf630a8819094455fc45a815b83 |
completed | May 8, 2026, 1:31 a.m. |
Created at: April 9, 2026, 5:29 p.m.