Triple
T14816536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Hanson |
E348331
|
entity |
| Predicate | relationshipTypeWithFemaleLead |
P115840
|
FINISHED |
| Object | best 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: best friend | Statement: [George Hanson, relationshipTypeWithFemaleLead, best friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithFemaleLead Context triple: [George Hanson, relationshipTypeWithFemaleLead, best friend]
-
A.
hasLeadCharacterGender
Indicates that the primary or lead character in a work has a specified gender.
-
B.
numberOfMainFemaleLeadsInWork
Indicates the number of primary female lead characters that appear in a given work.
-
C.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
D.
leadActorSexualOrientation
Indicates the sexual orientation of the lead actor in a work or production.
-
E.
maleLeadActor
Indicates that the subject is the primary male actor in a performance or production.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe2c1ec81908b3dff7a5d0e85d0 |
completed | April 14, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:49 a.m.