Triple
T5558313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fast of the Tenth of Tevet |
E145702
|
entity |
| Predicate | maritalRelations |
P64467
|
FINISHED |
| Object | permitted |
—
|
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: permitted | Statement: [Fast of the Tenth of Tevet, maritalRelations, permitted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritalRelations Context triple: [Fast of the Tenth of Tevet, maritalRelations, permitted]
-
A.
hasMaritalRelationshipType
Indicates the specific type or nature of the marital relationship that exists between two entities.
-
B.
spouseType
Indicates the specific role or category of a person within a spousal relationship (e.g., husband, wife, partner).
-
C.
maritalBasis
Indicates that the relationship or status in question is founded on, justified by, or determined due to a marital relationship between the involved entities.
-
D.
spouseFamily
Indicates a family relationship formed through marriage, such as between a person and their spouse’s relatives.
-
E.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0201529a88190bf0135e032b048ea |
completed | March 22, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69c01b10bbf8819098655839c03b7832 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0684908190ae2d14f0bd2ab892 |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:36 p.m.