Triple
T7904805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baby Herman |
E183544
|
entity |
| Predicate | occupationInUniverse |
P75042
|
FINISHED |
| Object | toon film star |
—
|
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: toon film star | Statement: [Baby Herman, occupationInUniverse, toon film star]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationInUniverse Context triple: [Baby Herman, occupationInUniverse, toon film star]
-
A.
employerInUniverse
Indicates that one entity serves as the employer of another within a specified universe, context, or world.
-
B.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
C.
roleInGalaxy
Indicates the specific function, status, or influence an entity holds within the broader structure or dynamics of a galaxy.
-
D.
occupationType
chosen
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
E.
occupationDuringAlias
Indicates that an entity held a particular occupation specifically during the time period when it was known by a given alias.
- 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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a4331cc8190b50301c78767a850 |
completed | March 31, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69cae92f9498819085277879e59aa072 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:03 p.m.