Triple
T11994991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin and Lewis |
E285505
|
entity |
| Predicate | performerRoleOfJerryLewis |
P102780
|
FINISHED |
| Object | comedian |
—
|
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: comedian | Statement: [Martin and Lewis, performerRoleOfJerryLewis, comedian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: performerRoleOfJerryLewis Context triple: [Martin and Lewis, performerRoleOfJerryLewis, comedian]
-
A.
performerCharacterName
Indicates that a performer is associated with or portrays a specific character name in a performance or work.
-
B.
MarilynMonroeRoleType
Indicates the type or category of role associated with Marilyn Monroe in a given context.
-
C.
performerCreditedAs
Indicates that a performer is associated with a work under a specific credited name or alias.
-
D.
characterPerformer
Indicates that a performer portrays or voices a particular character in a work.
-
E.
actorRole
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903b211688190bfe6dd15c3f96d2f |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d903a8695c8190bfa9d7ca50834f9f |
completed | April 10, 2026, 2:05 p.m. |
Created at: April 8, 2026, 9:46 p.m.