Triple
T31957325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Toy |
E815940
|
entity |
| Predicate | hasRelationshipTypeWithFrankToy |
P203617
|
FINISHED |
| Object | strained father-son relationship |
—
|
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: strained father-son relationship | Statement: [Joe Toy, hasRelationshipTypeWithFrankToy, strained father-son relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWithFrankToy Context triple: [Joe Toy, hasRelationshipTypeWithFrankToy, strained father-son relationship]
-
A.
isToyOf
Indicates that one entity is a toy that belongs to, is used by, or is associated with another entity.
-
B.
hasRelationshipTypeWith Fran Fine
Indicates that an entity is connected to Fran Fine by a specific, categorized type of relationship (e.g., familial, professional, romantic, or social).
-
C.
hasRelationshipTypeWith Frank Drebin
Indicates that there exists a specific type of relationship between an entity and Frank Drebin.
-
D.
hasRelationshipTypeWith Tai Frasier
Indicates that there exists a specific type of relationship between an entity and Tai Frasier.
-
E.
relationshipToToons
Indicates a relationship that specifies how an entity is connected or related to one or more cartoon or animated characters.
- 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_69f348f4ec708190abbb2a7c3ed58844 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a01b3af7b908190b4675c85d32d106c |
completed | May 11, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_6a01b35813c081908e484b2b9ca5dd05 |
completed | May 11, 2026, 10:45 a.m. |
| PDg | Predicate description generation | batch_6a01b3ae7f948190b93fbe0add0dbcec |
completed | May 11, 2026, 10:47 a.m. |
Created at: May 1, 2026, 12:08 a.m.