Triple
T27206888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma family army |
E683888
|
entity |
| Predicate | athleteBackground |
P118350
|
FINISHED |
| Object | many athletes recruited from rural China |
—
|
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: many athletes recruited from rural China | Statement: [Ma family army, athleteBackground, many athletes recruited from rural China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: athleteBackground Context triple: [Ma family army, athleteBackground, many athletes recruited from rural China]
-
A.
formerAthlete
Indicates that a person previously had the role or status of an athlete but no longer does.
-
B.
sportsIdentity
Indicates that an entity’s identity, role, or affiliation is defined in the context of sports (e.g., as an athlete, team, or sports-related organization).
-
C.
knownForSports
Indicates that an entity is recognized or notable for its involvement, achievement, or association with sports.
-
D.
sportsCareer
Indicates a relationship where an entity’s professional involvement, roles, or achievements in sports are associated with a particular sport, team, period, or competitive level.
-
E.
athleteRecruitmentFrom
chosen
Indicates that an athlete was recruited from a particular source, such as a school, team, or location.
- 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f625e6138c819093137c0d085b499b |
completed | May 2, 2026, 4:27 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 9:38 a.m.