Triple
T25551264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Phone Calls Featuring Neil Hamburger |
E640444
|
entity |
| Predicate | hasAlterEgoPerformer |
P86336
|
FINISHED |
| Object | Neil Hamburger |
—
|
NE NERFINISHED |
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: Neil Hamburger | Statement: [Great Phone Calls Featuring Neil Hamburger, hasAlterEgoPerformer, Neil Hamburger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlterEgoPerformer Context triple: [Great Phone Calls Featuring Neil Hamburger, hasAlterEgoPerformer, Neil Hamburger]
-
A.
hasRapAlterEgoOf
Indicates that one entity is the rap-stage persona or alter ego used by another entity.
-
B.
hasFictionalAlterEgoOf
chosen
Indicates that one entity is the fictional alter ego, persona, or alternate identity of another entity.
-
C.
hasAlterEgoCostume
Indicates that an entity has a distinct costume specifically associated with its alter ego identity.
-
D.
hasFictionalPerformer
Indicates that an entity is associated with a performer who is a fictional or imaginary character rather than a real person.
-
E.
hasAlterEgoDevice
Indicates that an entity possesses or is associated with a device specifically used to enable, support, or manifest its alter ego.
- 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_69e75dc101a881909fd33b02174e9768 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 3:36 p.m.