Triple
T5132173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Gilboa |
E115725
|
entity |
| Predicate | nearCity |
P350
|
FINISHED |
| Object | Beit She'an |
E148016
|
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: Beit She'an | Statement: [Mount Gilboa, nearCity, Beit She'an]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beit She'an Context triple: [Mount Gilboa, nearCity, Beit She'an]
-
A.
Beit She'an
chosen
Beit She'an is an ancient city in northeastern Israel known for its extensive archaeological remains, including a well-preserved Roman-Byzantine ruins complex.
-
B.
Kiryat Tiv'on
Kiryat Tiv'on is a town in northern Israel, near Haifa, known for its residential character and proximity to archaeological and natural sites.
-
C.
Yokneam Illit
Yokneam Illit is a city in northern Israel known for its high-tech industrial parks and rapid development from a small town into a regional technology hub.
-
D.
Beersheba
Beersheba is a major city in southern Israel, often regarded as the "Capital of the Negev" and known for its historical significance and rapid modern development.
-
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_69bd444426bc819099ccd23f141e22aa |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd784b477c8190926daddb28a255af |
completed | March 20, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf4110cbbc8190858ad55ac501a034 |
completed | March 22, 2026, 1:08 a.m. |
Created at: March 20, 2026, 1:42 p.m.