Triple
T28163441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan Keen |
E714957
|
entity |
| Predicate | Ann Keen |
P164086
|
FINISHED |
| Object | is also a British Labour Party politician |
—
|
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: is also a British Labour Party politician | Statement: [Alan Keen, Ann Keen, is also a British Labour Party politician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Ann Keen Context triple: [Alan Keen, Ann Keen, is also a British Labour Party politician]
-
A.
Mary Bell
Indicates a relationship or action involving an entity named Mary Bell, though the specific nature of the relationship or action is not defined by the predicate alone.
-
B.
Libby
Indicates a relationship or action involving Libby, though the specific nature of the relationship is not defined by the predicate name alone.
-
C.
née
Indicates that a person’s original birth name, typically a maiden name, is being specified before it was changed (for example, by marriage).
-
D.
Jack Hively
Indicates a relationship or action involving the person named Jack Hively, such as authorship, direction, or participation in a work or event.
-
E.
Diva
Indicates that an entity is characterized as a celebrated but temperamental performer, often demanding special treatment or attention in their professional context.
- 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_69efd6b156448190bfa15958208395c3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f641ed2a0c81909246ce42d3e01317 |
completed | May 2, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69f63c6c1a948190b68c0f92c264cc0c |
completed | May 2, 2026, 6:03 p.m. |
| PDg | Predicate description generation | batch_69f63fd4f7448190930c723ba7cfce62 |
completed | May 2, 2026, 6:17 p.m. |
Created at: April 27, 2026, 10:08 p.m.