Triple
T6343822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode Hebrew block |
E142695
|
entity |
| Predicate | containsCategory |
P70092
|
FINISHED |
| Object | letters |
—
|
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: letters | Statement: [Unicode Hebrew block, containsCategory, letters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsCategory Context triple: [Unicode Hebrew block, containsCategory, letters]
-
A.
hasCategoryWithin
Indicates that one category is contained within or is a subcategory of another category.
-
B.
hasCategoryOn
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
C.
haveCategoryCode
Indicates that an entity is associated with a specific classification or category identified by a code.
-
D.
hasRelatedCategory
Indicates that one category is associated with another category through a non-hierarchical, contextually relevant relationship.
-
E.
hasCategoryLevel
Indicates that something is associated with a specific hierarchical category or tier within a classification system.
- 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_69c008d5ab108190b346c465696824a9 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0674702d08190806ef0998960b797 |
completed | March 22, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69c060ea1a988190889e47b7e0c819b8 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:31 p.m.