Triple
T6610657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Markus Merk |
E149227
|
entity |
| Predicate | hasProfessionOutsideFootball |
P72439
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Markus Merk, hasProfessionOutsideFootball, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionOutsideFootball Context triple: [Markus Merk, hasProfessionOutsideFootball, yes]
-
A.
hasPlayedProfessionalSports
Indicates that an entity has participated as an athlete in an officially recognized professional-level sports competition or league.
-
B.
hasNotableProfessionField
Indicates that an entity’s notable profession or occupation belongs to a particular professional field or domain.
-
C.
hasCoachedProfessionalSports
Indicates that a person has served in a coaching role for a professional-level sports team or athlete.
-
D.
hasProfessionalLeague
Indicates that an entity is associated with or participates in a recognized professional sports league.
-
E.
includesProfession
Indicates that one entity’s set of attributes, roles, or members contains a specific profession as part of it.
- 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_69c687ebc680819094caf71faba2efe2 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cf3796d08190a26e988386089447 |
completed | March 27, 2026, 6:40 p.m. |
| PD | Predicate disambiguation | batch_69c6acfed25481909cac74c84a9fe088 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6cf3683d08190b19e2aad30f2800f |
completed | March 27, 2026, 6:40 p.m. |
Created at: March 27, 2026, 1:57 p.m.