Triple
T16190148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandler family |
E392912
|
entity |
| Predicate | hasRelativeWorkingIn |
P102232
|
FINISHED |
| Object | comedy films |
—
|
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: comedy films | Statement: [Sandler family, hasRelativeWorkingIn, comedy films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelativeWorkingIn Context triple: [Sandler family, hasRelativeWorkingIn, comedy films]
-
A.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
-
B.
hasWorksIn
Indicates that one entity is employed by or performs their professional activities within the organization, location, or context represented by another entity.
-
C.
hasWorkedFor
Indicates that an entity has been employed by or has provided work or services to another entity.
-
D.
hasOccupationRelative
chosen
Indicates that one entity has another entity as a relative who holds a particular occupation or job.
-
E.
hasRelationshipToWork
Indicates a relationship where an entity has a specific connection, role, or association with a particular work or piece of work.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222d4ab8081909a02e5138b29b83b |
completed | April 17, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69e219e11f6081909106b1240a17fd37 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.