Triple
T9871777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee Eastman |
E239972
|
entity |
| Predicate | relationshipToSubject |
P84787
|
FINISHED |
| Object | father-in-law of Paul McCartney |
—
|
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: father-in-law of Paul McCartney | Statement: [Lee Eastman, relationshipToSubject, father-in-law of Paul McCartney]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToSubject Context triple: [Lee Eastman, relationshipToSubject, father-in-law of Paul McCartney]
-
A.
subjectRelation
chosen
Indicates that one entity stands in a specified relational role or connection to another entity.
-
B.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
C.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
-
D.
editorRelationshipToSubject
Indicates that one entity serves as an editor for, or has an editorial role or responsibility in relation to, the subject entity.
-
E.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
- 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_69ca84e7506c819095cbde4ff16512bb |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3f5cc948190b03186b867c92229 |
completed | April 2, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:36 p.m.