Triple
T26501083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adrian, Earl of Windsor |
E669422
|
entity |
| Predicate | relationshipTypeWith Lionel Verney |
P197017
|
FINISHED |
| Object | close friend |
—
|
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: close friend | Statement: [Adrian, Earl of Windsor, relationshipTypeWith Lionel Verney, close friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Lionel Verney Context triple: [Adrian, Earl of Windsor, relationshipTypeWith Lionel Verney, close friend]
-
A.
relationshipTypeWithLuciousLyon
Indicates the specific nature or category of relationship that an entity has with Lucious Lyon.
-
B.
relationshipTypeWithLily Owens
Indicates the specific nature or category of relational connection that an entity has with Lily Owens.
-
C.
relationshipTypeWithLorraineBroughton
Indicates the specific nature or category of relationship an entity has with Lorraine Broughton.
-
D.
relationshipTypeWith Mona Stangley
Indicates the specific type or nature of relationship that an entity has with Mona Stangley.
-
E.
relationshipTypeWithLouisLitt
Indicates the specific nature or category of relationship that an entity has with Louis Litt.
- 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_69eeb319ec70819090834c2591cf5f1e |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69fe744faca881908e11e90e0a35653f |
completed | May 8, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69fe734cbf7081909a552c5cf3b5ea59 |
completed | May 8, 2026, 11:35 p.m. |
| PDg | Predicate description generation | batch_69fe744e9ee081909b362fc8609bc744 |
completed | May 8, 2026, 11:39 p.m. |
Created at: April 27, 2026, 1:13 a.m.