Triple
T10370704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Recceswinth |
E244373
|
entity |
| Predicate | legalCodeAudience |
P90195
|
FINISHED |
| Object | all free inhabitants of the kingdom |
—
|
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: all free inhabitants of the kingdom | Statement: [Recceswinth, legalCodeAudience, all free inhabitants of the kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalCodeAudience Context triple: [Recceswinth, legalCodeAudience, all free inhabitants of the kingdom]
-
A.
legalCodeType
Indicates the specific category or classification of a legal code that applies to an entity or situation.
-
B.
legalCodeAppliesTo
chosen
Indicates that a particular legal code or statute is applicable to, or governs, a specified subject, situation, or entity.
-
C.
legalCodeName
Indicates that one entity is the official legal code designation or name assigned to another entity within a legal or regulatory system.
-
D.
usesLegalCode
Indicates that one entity applies, references, or operates under a particular legal code in its actions or regulations.
-
E.
legalCodeFocus
Indicates that something is specifically concerned with, centered on, or primarily addressing a particular legal code or body of law.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9737cfc81909d6302bd4177d186 |
completed | April 7, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69d4dface5508190a7b42f01ad0a19a2 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 12:01 p.m.