Triple
T27146799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | נצרת עילית |
E681971
|
entity |
| Predicate | הוקמה בסמוך ל |
P42067
|
FINISHED |
| Object | נצרת הערבית |
—
|
NE NERFINISHED |
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: נצרת הערבית | Statement: [נצרת עילית, הוקמה בסמוך ל, נצרת הערבית]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: הוקמה בסמוך ל Context triple: [נצרת עילית, הוקמה בסמוך ל, נצרת הערבית]
-
A.
foundedNear
chosen
Indicates that one entity established or created another entity at a location geographically close to a specified reference entity or place.
-
B.
locatedNearFormer
Indicates that one entity is situated close to another entity that previously occupied a nearby or the same location.
-
C.
historicallyLocatedNear
Indicates that, in a historical context, one entity was geographically situated close to another entity.
-
D.
locatedNearHazard
Indicates that one entity is situated in close physical proximity to a hazardous object, area, or condition.
-
E.
oftenLocatedNear
Indicates that one entity is frequently found in close physical proximity to 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_69eefacca3888190b67238d380e8f28b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f624c6dff08190ba0573eba9d63449 |
completed | May 2, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 9:11 a.m.