Triple
T22251837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Fielding |
E549998
|
entity |
| Predicate | relationshipTypeWithDrAziz |
P10690
|
FINISHED |
| Object | friendship |
—
|
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: friendship | Statement: [Richard Fielding, relationshipTypeWithDrAziz, friendship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithDrAziz Context triple: [Richard Fielding, relationshipTypeWithDrAziz, friendship]
-
A.
relationshipToAmir
Indicates that one entity has a specified personal, social, or familial relationship to the person Amir.
-
B.
associatedPersonRelationToMuhammad
Indicates the specific type of relationship or connection a person has to Muhammad.
-
C.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
relationshipTypeWithSassi
Indicates the specific type or nature of the relationship that an entity has with Sassi.
-
E.
relationshipToRa
Indicates a specified type of relational connection that an entity has to the entity Ra.
- 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_69e11e41d9408190bd770cf282e22753 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138befa208190877760dec1896740 |
completed | April 28, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69e72fe1e0cc8190bd13cff2a0846225 |
completed | April 21, 2026, 8:05 a.m. |
Created at: April 16, 2026, 8:39 p.m.