Triple
T2652176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shamash |
E53924
|
entity |
| Predicate | countingRule |
P41948
|
FINISHED |
| Object | not counted among the eight primary Hanukkah lights |
—
|
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: not counted among the eight primary Hanukkah lights | Statement: [Shamash, countingRule, not counted among the eight primary Hanukkah lights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countingRule Context triple: [Shamash, countingRule, not counted among the eight primary Hanukkah lights]
-
A.
numberOfRulesPlanned
Indicates the planned or intended count of rules associated with an entity or process.
-
B.
compositionRule
Indicates how multiple elements or components are combined or arranged according to a specific rule or pattern.
-
C.
principlesCount
Indicates the number of principles associated with or applicable to a given entity or context.
-
D.
isRuleGoverned
Indicates that an entity’s behavior, structure, or operation is determined and constrained by explicit rules or formal regulations.
-
E.
cardinality
Indicates the number of distinct elements or members in a given set or collection.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abda0ba2208190ad87763ecbef8c3c |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd815d06481909535c02b0aba8553 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abda0a13308190a986df86270258a7 |
completed | March 7, 2026, 7:55 a.m. |
Created at: March 6, 2026, 9:53 p.m.