Triple
T1191830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon Sharpe |
E25378
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Shannon |
E3529
|
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: Shannon | Statement: [Shannon Sharpe, givenName, Shannon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shannon Context triple: [Shannon Sharpe, givenName, Shannon]
-
A.
Shannon
chosen
Shannon is a common Irish surname that originates from the River Shannon and is borne by numerous notable individuals, including mathematician and information theorist Claude Shannon.
-
B.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
-
C.
Tracy
Tracy is a given name commonly used for both males and females in English-speaking countries.
-
D.
Tracy
Tracy is a city in California’s Central Valley known as a growing suburban community within the San Francisco Bay Area’s commuter belt.
-
E.
Lynn
Lynn is a coastal city in northeastern Massachusetts, known as one of the larger urban centers in the Greater Boston metropolitan area.
- 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd74e2c08190b4a48425f94addaa |
completed | March 1, 2026, 10:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac764ea588819082f7d5d0e44e1211 |
completed | March 7, 2026, 7:02 p.m. |
Created at: March 1, 2026, 7:45 p.m.