Triple
T28305592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maalik Wayns |
E713834
|
entity |
| Predicate | playedProfessionalOverseas |
P99007
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Maalik Wayns, playedProfessionalOverseas, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedProfessionalOverseas Context triple: [Maalik Wayns, playedProfessionalOverseas, true]
-
A.
hasPlayedOverseas
chosen
Indicates that an individual has participated in their professional or competitive activity in a country other than their home country.
-
B.
playedInternationally
Indicates that an individual has participated in official international-level events or competitions representing a country or equivalent national entity.
-
C.
hasPlayedProfessionalSports
Indicates that an entity has participated as an athlete in an officially recognized professional-level sports competition or league.
-
D.
hasProfessionalLeague
Indicates that an entity is associated with or participates in a recognized professional sports league.
-
E.
hasPlayedInCountry
Indicates that an entity (typically a person or team) has participated in a game, match, or performance within a specified country.
- 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_69efb5256afc8190b9322d25c3ae6320 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: April 27, 2026, 11:37 p.m.