Triple
T15340778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Chacal |
E366787
|
entity |
| Predicate | amateurRecord |
P48766
|
FINISHED |
| Object | highly successful Cuban amateur career |
—
|
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: highly successful Cuban amateur career | Statement: [El Chacal, amateurRecord, highly successful Cuban amateur career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: amateurRecord Context triple: [El Chacal, amateurRecord, highly successful Cuban amateur career]
-
A.
amateurAchievement
Indicates that an entity has achieved something notable or commendable in a non-professional or hobbyist capacity.
-
B.
amateurCareerRecord
chosen
Indicates the win–loss (and possibly draw) record an individual achieved during their amateur-level career in a given activity or sport.
-
C.
amateurTitle
Indicates that an entity holds or is associated with a non-professional (amateur) title or rank in a given domain or activity.
-
D.
amateurParticipants
Indicates that the participants involved in the event or activity are amateurs rather than professionals.
-
E.
amateurEra
Indicates that the subject participated in or was associated with an amateur phase or period, as opposed to a professional one.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e12eb7c8190944a260aa1aa9156 |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca991e5081908b0df3d1ee7d5338 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:17 a.m.