Triple
T7292511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Turim |
E164430
|
entity |
| Predicate | EvenHaEzerScope |
P75429
|
FINISHED |
| Object | marriage and family law |
—
|
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: marriage and family law | Statement: [The Turim, EvenHaEzerScope, marriage and family law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EvenHaEzerScope Context triple: [The Turim, EvenHaEzerScope, marriage and family law]
-
A.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
B.
HethIs
Indicates that one entity is identified as or equated with another entity, expressing a basic “is” or “being” relationship between them.
-
C.
hasFemaleEquivalent
Indicates that one entity serves as the female counterpart or equivalent of another entity.
-
D.
hasFair
Indicates that an entity organizes, hosts, or is associated with a fair or similar event.
-
E.
canBeSeenWith
Indicates that two entities are observable together in the same context, setting, or time.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb6fc5788190b1b339d051f93c22 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76c5fbc8190b378830082f11cb0 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6e82b0f9881909d29c99af1ea0dbf |
completed | March 27, 2026, 8:27 p.m. |
Created at: March 27, 2026, 3 p.m.