Triple
T19003044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andre Joubert |
E465003
|
entity |
| Predicate | hasNotableTeammate |
P2649
|
FINISHED |
| Object | Joel Stransky |
—
|
NE NERFINISHED |
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: Joel Stransky | Statement: [Andre Joubert, hasNotableTeammate, Joel Stransky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joel Stransky Context triple: [Andre Joubert, hasNotableTeammate, Joel Stransky]
-
A.
Joel Stransky
chosen
Joel Stransky is a former South African rugby union fly-half best known for kicking the winning drop goal in the 1995 Rugby World Cup final.
-
B.
Joel Springer
Joel Springer is known primarily as the husband of award-winning American mystery and fantasy author Nancy Springer.
-
C.
Joel Bergman
Joel Bergman was an American architect best known for designing iconic, large-scale casino resorts in Las Vegas.
-
D.
Joel Berez
Joel Berez is an American businessman best known as a co-founder and early leader of the pioneering interactive fiction game company Infocom.
-
E.
Joel Stillerman
Joel Stillerman is a television and film executive and producer known for his influential programming roles at networks like AMC and Hulu.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd01a56c81909694a128c66b21d7 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6a252588190a40398b1879fb096 |
completed | April 20, 2026, 7:32 a.m. |
Created at: April 10, 2026, 12:01 p.m.