Triple
T13787678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WTVT |
E331306
|
entity |
| Predicate | formerNetworkAffiliation |
P1168
|
FINISHED |
| Object |
CBS
CBS is a major American broadcast television network known for its wide range of news, sports, and entertainment programming.
|
E6070
|
NE FINISHED |
How this triple was built (4 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: CBS | Statement: [WTVT, formerNetworkAffiliation, CBS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CBS Context triple: [WTVT, formerNetworkAffiliation, CBS]
-
A.
CBS
CBS is a leading Danish university in Copenhagen specializing in business and economics education and research.
-
B.
CBS
CBS is a leading graduate business school of Columbia University in New York City, renowned for its MBA and finance programs.
-
C.
CBS
CBS is a college within the University of California, Davis that focuses on education and research in the biological sciences.
-
D.
CBS
CBS is a Harvard University research center dedicated to advancing the understanding of the brain through interdisciplinary neuroscience studies.
-
E.
CBS
CBS is the commonly used abbreviation for the Commission for Basic Systems, a specialized body focused on foundational infrastructure and standards, likely within an international or governmental organizational context.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: CBS Triple: [WTVT, formerNetworkAffiliation, CBS]
Generated description
CBS is a major American broadcast television network known for its wide range of news, sports, and entertainment programming.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CBS Target entity description: CBS is a major American broadcast television network known for its wide range of news, sports, and entertainment programming.
-
A.
CBS
chosen
CBS is a major American broadcast television network known for airing a wide range of popular news, sports, and entertainment programming nationwide.
-
B.
CBS
CBS is a leading graduate business school of Columbia University in New York City, renowned for its MBA and finance programs.
-
C.
CBS
CBS is the national statistical office of the Netherlands responsible for collecting, analyzing, and publishing data on the country’s economy, population, and society.
-
D.
CBS
CBS is the commonly used abbreviation for the Commission for Basic Systems, a specialized body focused on foundational infrastructure and standards, likely within an international or governmental organizational context.
-
E.
CBS
CBS is a college within the University of California, Davis that focuses on education and research in the biological sciences.
- F. None of above.
Provenance (5 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0249e4f88190a80316394940627d |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b07b0b2881909b316e3cc67f1ec1 |
completed | May 3, 2026, 8:30 p.m. |
| NEDg | Description generation | batch_69f7b138158c8190957d43d529c37fa4 |
completed | May 3, 2026, 8:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7b1e0ab948190a046a68aa5e029a6 |
completed | May 3, 2026, 8:36 p.m. |
Created at: April 9, 2026, 10:11 p.m.