Triple
T28833506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beit Furik |
E728114
|
entity |
| Predicate | hasOliveGroves |
P165646
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Beit Furik, hasOliveGroves, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOliveGroves Context triple: [Beit Furik, hasOliveGroves, true]
-
A.
hasVineyards
Indicates that one entity possesses, contains, or is associated with vineyards used for growing grapevines.
-
B.
hasVineyardsNear
Indicates that one entity possesses or is associated with vineyards located in close geographic proximity to another entity.
-
C.
hasWinemakingFacility
Indicates that an entity possesses or is associated with a facility where winemaking activities are carried out.
-
D.
cultivatedBy
Indicates that something (such as land, crops, or plants) is grown, tended, or developed through the efforts or care of a particular agent.
-
E.
alsoProducesWineIn
Indicates that the subject, in addition to other products or activities, produces wine in the specified location or context.
- 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_69f0319dc6088190bbfaa206d40ed74a |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f6596b210481908af6cd555748f75b |
completed | May 2, 2026, 8:07 p.m. |
| PD | Predicate disambiguation | batch_69f65762b5e481908a30ca963dcba4be |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f658ebeca4819096beb3f98f73fe31 |
completed | May 2, 2026, 8:05 p.m. |
Created at: April 28, 2026, 6:38 a.m.