Triple
T21610844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lina McLaidlaw Aysgarth |
E533300
|
entity |
| Predicate | relationshipToBeaky |
P144775
|
FINISHED |
| Object | friend of her husband’s 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: friend of her husband’s friend | Statement: [Lina McLaidlaw Aysgarth, relationshipToBeaky, friend of her husband’s friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToBeaky Context triple: [Lina McLaidlaw Aysgarth, relationshipToBeaky, friend of her husband’s friend]
-
A.
relationshipToBenny
Indicates the specific type of personal or social relationship that an entity has with Benny.
-
B.
relationshipToKenny
Indicates the specific familial, social, or interpersonal connection that one entity has to Kenny.
-
C.
relationshipToBoDecker
Indicates the specific type of personal or social relationship an entity has with Bo Decker.
-
D.
relationToBabo
Indicates a relationship or connection that an entity has to the person or entity referred to as "Babo."
-
E.
relationshipToAkeem
Indicates the specific type of personal or social relationship that an entity has with Akeem.
- 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_69e0c46411108190bba0d4176dffc9f3 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef17e88f7081909371bc0de2147609 |
completed | April 27, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69e69665fe8c8190af7e38785db188b2 |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69b4aa2b48190830107391e81571a |
completed | April 20, 2026, 9:31 p.m. |
Created at: April 16, 2026, 6:33 p.m.