Triple
T556715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gloucester (former local government area) |
E11956
|
entity |
| Predicate | formerType |
P16344
|
FINISHED |
| Object | local government area |
—
|
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: local government area | Statement: [Gloucester (former local government area), formerType, local government area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerType Context triple: [Gloucester (former local government area), formerType, local government area]
-
A.
formerName
Indicates that an entity was previously known by a different name in the past.
-
B.
formerFunction
Indicates that an entity previously held a specific role, position, or function but no longer does so.
-
C.
originalType
Indicates that one entity represents the initial or source type from which another entity is derived, transformed, or reclassified.
-
D.
formerDesignation
Indicates that an entity previously held a particular title, role, or designation that it no longer holds.
-
E.
originalForm
Indicates that one entity is the earlier, source, or initial version from which another entity is derived or transformed.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4991ef9b0819092ec0407270373f4 |
completed | March 1, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69a494bd78e8819083c519669158f209 |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985952a481908b918350ececf484 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.