Triple
T25529302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mischief Farm |
E639866
|
entity |
| Predicate | hasCoOwnerProfession |
P184351
|
FINISHED |
| Object | television actor |
—
|
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: television actor | Statement: [Mischief Farm, hasCoOwnerProfession, television actor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoOwnerProfession Context triple: [Mischief Farm, hasCoOwnerProfession, television actor]
-
A.
hasCoOwner
Indicates that an entity shares ownership of something with one or more other entities.
-
B.
isAssociatedWithProfessionOfBearer
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
C.
partnerInProfession
Indicates that two or more entities share a professional partnership or collaborate together within the same occupation or field.
-
D.
hasProfessionalRelationshipWith
Indicates a formal, work-related connection or collaboration exists between the two entities in a professional context.
-
E.
ownerProfession
Indicates that the profession or occupation is associated with, or held by, the owner of a specified entity.
- 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_69e75dbf3f9c8190b3f2a75d1b75d127 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7b0e3917481908a394680d76743c3 |
completed | May 3, 2026, 8:32 p.m. |
Created at: April 21, 2026, 3:13 p.m.