Triple
T8410127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 NBA All-Star Game |
E198600
|
entity |
| Predicate | loser |
P356
|
FINISHED |
| Object | Team Stephen |
E731498
|
NE 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: Team Stephen | Statement: [2018 NBA All-Star Game, loser, Team Stephen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Team Stephen Context triple: [2018 NBA All-Star Game, loser, Team Stephen]
-
A.
Team Stephen
chosen
Team Stephen was one of the two squads in the 2018 NBA All-Star Game, captained and drafted by Stephen Curry from a pool of selected All-Star players.
-
B.
The Team
The Team is the English translation of "Die Mannschaft," the widely used nickname for the German national football team.
-
C.
Team Gray
Team Gray was a robotics team that gained recognition for competing in DARPA’s pioneering autonomous vehicle Grand Challenge.
-
D.
Team Fuqua
Team Fuqua is the collaborative, team-oriented culture and community ethos that defines the student and alumni experience at Duke University's Fuqua School of Business.
-
E.
Team 4
Team 4 is an architectural group best known for its influential early work in high-tech architecture, whose members included Su Rogers and other future leaders of the field.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83dec1f08190ae08719e860b29fa |
completed | March 31, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1d34214481908503c662eb060ff7 |
completed | April 2, 2026, 7:39 a.m. |
Created at: March 30, 2026, 6:05 p.m.