Triple
T935375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Decalogue |
E20182
|
entity |
| Predicate | hasDifferentEnumerationsIn |
P21763
|
FINISHED |
| Object | Jewish tradition |
—
|
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: Jewish tradition | Statement: [Decalogue, hasDifferentEnumerationsIn, Jewish tradition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDifferentEnumerationsIn Context triple: [Decalogue, hasDifferentEnumerationsIn, Jewish tradition]
-
A.
isDistinctFrom
Indicates that two entities are not identical and can be clearly distinguished from one another.
-
B.
hasDistinctFeature
Indicates that an entity possesses a specific characteristic or attribute that differentiates it from others.
-
C.
hasEquivalent
Indicates that two entities are considered equal in value, meaning, or function within a given context.
-
D.
hasDistinctCharacterSet
Indicates that two compared items use different sets of characters, with no character set being a subset or duplicate of the other.
-
E.
hasGrammarDifferenceFrom
Indicates that two linguistic items differ from each other in their grammatical form, structure, or rules of usage.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b36558588190a2a9c710073624d1 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29b245c8190b143f28b77fede3c |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.