Triple
T4637564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hundred of Northwich |
E101569
|
entity |
| Predicate | partOfLegalSystem |
P57899
|
FINISHED |
| Object | historic English local government structure |
—
|
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: historic English local government structure | Statement: [Hundred of Northwich, partOfLegalSystem, historic English local government structure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfLegalSystem Context triple: [Hundred of Northwich, partOfLegalSystem, historic English local government structure]
-
A.
relatedLegalSystem
Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
-
B.
legalSystem
Indicates the formal framework of laws, rules, and institutions that governs how legal matters are defined, interpreted, and enforced within a society or jurisdiction.
-
C.
separateLegalSystem
Indicates that one entity maintains its own distinct and independent legal system from another entity.
-
D.
legalSystemWorkedIn
Indicates that a person carried out their professional legal activities within a particular legal system or jurisdiction.
-
E.
legalSystemDepictedAs
Indicates that one entity portrays, represents, or characterizes a legal system in a particular way or form.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a64214481908a207e8070cc7a45 |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5233cb5081908807e2b150f0ca06 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56f7b94481909f3335312becd446 |
completed | March 20, 2026, 2:17 p.m. |
Created at: March 20, 2026, 1:13 p.m.