Triple
T23853137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sukkah |
E592226
|
entity |
| Predicate | hasWallRequirement |
P154195
|
FINISHED |
| Object | minimum of two full walls and a partial third wall according to halakha |
—
|
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: minimum of two full walls and a partial third wall according to halakha | Statement: [Sukkah, hasWallRequirement, minimum of two full walls and a partial third wall according to halakha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWallRequirement Context triple: [Sukkah, hasWallRequirement, minimum of two full walls and a partial third wall according to halakha]
-
A.
hasWall
Indicates that one entity possesses, includes, or is bounded by a wall.
-
B.
hasWallType
Indicates the specific kind or classification of wall associated with an entity.
-
C.
hasWallLayer
Indicates that one entity includes or is associated with a specific layer within a wall structure.
-
D.
hasWallShape
Indicates that an entity possesses a wall whose form or outline matches a specified geometric or structural shape.
-
E.
hasWallsMaterial
Indicates that the material specified is used to construct or cover the walls of the referenced entity.
- 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_69e25d221d908190b9b502ad31e66a3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c9887e5c819089437769acf684c4 |
completed | April 29, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e348b548190b76e50f9b611f76d |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 8:11 p.m.