Triple
T513430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dennis Johnson |
E10654
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Dennis |
E7519
|
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: Dennis | Statement: [Dennis Johnson, givenName, Dennis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dennis Context triple: [Dennis Johnson, givenName, Dennis]
-
A.
Dennis
chosen
Dennis is a coastal town on Cape Cod in Massachusetts known for its beaches, historic charm, and popular summer tourism.
-
B.
Dustin
Dustin is a masculine given name commonly used in English-speaking countries.
-
C.
Gordon
Gordon is the middle name of the famed Romantic poet Lord Byron, whose full name is George Gordon Byron.
-
D.
Kenneth
Kenneth is the formal given name of American country music singer, songwriter, and actor Kenny Rogers.
-
E.
Don
The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1804e908190a1d34ac952e84a3f |
completed | Feb. 28, 2026, 1:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4fc7b283c8190af5fb7fa649a9095 |
completed | March 2, 2026, 2:56 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.