Triple
T27164390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Campaign for Equality |
E682742
|
entity |
| Predicate | legalDomainTargeted |
P19463
|
FINISHED |
| Object | 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: family law | Statement: [Campaign for Equality, legalDomainTargeted, family law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalDomainTargeted Context triple: [Campaign for Equality, legalDomainTargeted, family law]
-
A.
legalTarget
Indicates that an action, decision, or rule is directed toward an entity in a manner that is permitted or recognized as valid under the governing legal or rule system.
-
B.
hasLegalDomain
chosen
Indicates that a legal rule, right, obligation, or concept applies within a specific jurisdiction, legal system, or domain of law.
-
C.
inputDomain
Indicates that a function, process, or system accepts inputs belonging to a specified domain or set of allowable values.
-
D.
territorialDomain
Indicates that one entity has territorial authority, control, or jurisdiction over a geographic area or domain associated with another entity.
-
E.
domainServed
Indicates that a particular domain or area is supported, covered, or provided for by a given entity or service.
- F. None of above.
Provenance (3 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_69eefacf6e788190a75a64399d9e3109 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: April 27, 2026, 9:20 a.m.