Triple
T112955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orthodox Judaism |
E2285
|
entity |
| Predicate | hasText |
P7166
|
FINISHED |
| Object | Shulchan Aruch as a central legal code |
—
|
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: Shulchan Aruch as a central legal code | Statement: [Orthodox Judaism, hasText, Shulchan Aruch as a central legal code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasText Context triple: [Orthodox Judaism, hasText, Shulchan Aruch as a central legal code]
-
A.
hasTextOpening
Indicates that an entity begins with or contains a specified initial segment of text.
-
B.
hasTerm
Indicates that an entity includes, is associated with, or is defined by a specific term or condition.
-
C.
hasBasicLetters
Indicates that an entity contains or is composed of fundamental alphabetic characters, without additional symbols or diacritics.
-
D.
hasLogoText
Indicates that an entity’s logo includes specific textual content or wording.
-
E.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256425a488190959d71e39e699d90 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2587e598c81909e1082b813971f48 |
completed | Feb. 28, 2026, 2:52 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.