Triple
T12536204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walton |
E299695
|
entity |
| Predicate | hasCivilStatus |
P105779
|
FINISHED |
| Object | civil parish |
—
|
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: civil parish | Statement: [Walton, hasCivilStatus, civil parish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCivilStatus Context triple: [Walton, hasCivilStatus, civil parish]
-
A.
civicStatus
Indicates the legal or social standing of an individual within a civic or societal framework, such as marital or citizenship status.
-
B.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
C.
marriageLegalStatus
Indicates the legal status of a marriage relationship between entities, such as whether it is valid, invalid, pending, or dissolved under applicable law.
-
D.
spouseStatus
Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
-
E.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d95f5148948190946a575d812b329d |
completed | April 10, 2026, 8:36 p.m. |
Created at: April 8, 2026, 9:57 p.m.