Triple
T6530093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CM Punk |
E152208
|
entity |
| Predicate | otherProfession |
P69514
|
FINISHED |
| Object | mixed martial artist |
—
|
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: mixed martial artist | Statement: [CM Punk, otherProfession, mixed martial artist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherProfession Context triple: [CM Punk, otherProfession, mixed martial artist]
-
A.
relatedProfession
Indicates that two entities have professions that are connected or associated in some meaningful way, such as being in the same field, industry, or professional domain.
-
B.
includesProfession
chosen
Indicates that one entity’s set of attributes, roles, or members contains a specific profession as part of it.
-
C.
otherWork
Indicates that one work is related to another work by the same creator, but is distinct from the primary or referenced work.
-
D.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
E.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
- 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_69c688048ec8819093a47f7d332e12ec |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6adac53b0819097fece48a75cc48f |
completed | March 27, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69c68abd9c7c819099e4fe8097cd1b28 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:46 p.m.