Triple
T5230113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon Lucid |
E118088
|
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 Lucid, givenName, Shannon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shannon Context triple: [Shannon Lucid, 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.
Shannon
Shannon is a small rural town in the Manawatū-Whanganui region of New Zealand’s North Island.
-
C.
Vinton
Vinton is the given name of Vinton Cerf, an American computer scientist widely recognized as one of the "fathers of the Internet."
-
D.
Vinton
Vinton is a small village in western Texas, located near the city of El Paso and the U.S.–Mexico border.
-
E.
Sibert
Sibert is the given middle name of the renowned American novelist Willa Cather, known for her depictions of frontier life on the Great Plains.
- 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_69bd4466fb8c819083b806a79414d7e4 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7ae006ec8190abd23f650ca5bf53 |
completed | March 20, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe604a848190a3f6cc90185b3ca2 |
completed | March 21, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:48 p.m.