Triple
T33929277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lovemore N’dou |
E869839
|
entity |
| Predicate | postBoxingCareer |
P177918
|
FINISHED |
| Object | practising lawyer in Sydney |
—
|
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: practising lawyer in Sydney | Statement: [Lovemore N’dou, postBoxingCareer, practising lawyer in Sydney]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postBoxingCareer Context triple: [Lovemore N’dou, postBoxingCareer, practising lawyer in Sydney]
-
A.
formerBoxer
Indicates that a person previously worked or competed as a boxer but no longer does so.
-
B.
yearsActiveAsBoxer
Indicates the span of time, measured in years, during which an individual was actively engaged in boxing.
-
C.
undefeatedInProfessionalBoxing
Indicates that a boxer has never lost any match in their professional boxing career.
-
D.
activeYearsInBoxingPromotion
Indicates the span of years during which an entity was actively involved with a particular boxing promotion.
-
E.
boxingRecordSummary
Indicates the summarized outcome or performance record of an entity in boxing matches, such as total wins, losses, and related statistics.
- 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_69f3499a59788190bff762a891471b31 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69f7064d37388190993b2a7305a02b9f |
completed | May 3, 2026, 8:24 a.m. |
Created at: May 1, 2026, 1:49 a.m.