Triple
T11531577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Costa |
E273433
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | PBS |
E8587
|
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: PBS | Statement: [Robert Costa, employer, PBS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PBS Context triple: [Robert Costa, employer, PBS]
-
A.
PBS
PBS is a U.S. federal agency component responsible for managing and providing government office space and real property for civilian agencies.
-
B.
PBS
chosen
PBS is a U.S. public television network known for educational, scientific, and cultural programming.
-
C.
American Public Television
American Public Television is a major U.S. syndicator and distributor of public television programming, providing content and services to public TV stations nationwide.
-
D.
CBS
CBS is a major American broadcast television network known for airing a wide range of popular news, sports, and entertainment programming nationwide.
-
E.
CBS
CBS is a leading Danish university in Copenhagen specializing in business and economics education and research.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8839878948190b170e64629d6f2db |
completed | April 10, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6856341b481909d2ee71893e6117b |
completed | April 20, 2026, 7:58 p.m. |
Created at: April 8, 2026, 9:37 p.m.