Triple
T10402484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marv Albert |
E245180
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | TBS |
E3613
|
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: TBS | Statement: [Marv Albert, employer, TBS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TBS Context triple: [Marv Albert, employer, TBS]
-
A.
TBS
chosen
TBS is an American cable television network known for airing comedy programming, movies, and major sports events, including NCAA Division I Men’s Basketball Tournament games.
-
B.
TBS
TBS is the United States Marine Corps’ primary officer training and education institution where newly commissioned officers learn the fundamentals of leading Marines.
-
C.
TBS
TBS is the three-letter IATA airport code for Tbilisi International Airport, serving the capital city of Georgia.
-
D.
TBS
TBS is a major Japanese television network known for broadcasting popular anime and drama series.
-
E.
TBS
TBS is a major Japanese television network known for broadcasting a wide range of anime, dramas, and variety programs.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9e42da08190a5383df3df6d3c18 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fbd13c888190b3a79a9aacb5291e |
completed | April 9, 2026, 7:19 p.m. |
Created at: April 6, 2026, 12:08 p.m.