Triple
T8410137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 NBA All-Star Game |
E198600
|
entity |
| Predicate | televisionNetworkUS |
P833
|
FINISHED |
| Object | TNT |
E3614
|
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: TNT | Statement: [2018 NBA All-Star Game, televisionNetworkUS, TNT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TNT Context triple: [2018 NBA All-Star Game, televisionNetworkUS, TNT]
-
A.
TNT
chosen
TNT is an American cable television network known for airing sports, movies, and original drama programming.
-
B.
TNT
TNT is France's digital terrestrial television platform that broadcasts multiple free-to-air channels nationwide.
-
C.
Tank
Tank is a German aeronautical engineer best known for designing the Focke-Wulf Fw 190 fighter aircraft used by the Luftwaffe during World War II.
-
D.
Tank
Tank is a London-based art and fashion magazine known for its independent, avant-garde editorial approach and collaborations with experimental cultural projects.
-
E.
Nuke
Nuke is the brash, hard-throwing rookie pitcher from the baseball film "Bull Durham," known for his wild talent and colorful personality.
- 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_69ce0317cb188190b207bcaffb629a75 |
completed | April 2, 2026, 5:48 a.m. |
Created at: March 30, 2026, 6:05 p.m.