Triple
T1663344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denis Potvin |
E35957
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Denis |
E74174
|
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: Denis | Statement: [Denis Potvin, givenName, Denis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denis Context triple: [Denis Potvin, givenName, Denis]
-
A.
Denis
chosen
Denis is a masculine given name of French origin, famously borne by the Enlightenment philosopher Denis Diderot.
-
B.
Dennis
Dennis is a coastal town on Cape Cod in Massachusetts known for its beaches, historic charm, and popular summer tourism.
-
C.
Jeffrey
Jeffrey is a masculine given name of Germanic origin, commonly used in English-speaking countries.
-
D.
Boris
Boris is the given name of Boris Johnson, the former Prime Minister of the United Kingdom and prominent British Conservative politician.
-
E.
Kenneth
Kenneth is the formal given name of American country music singer, songwriter, and actor Kenny Rogers.
- 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_69a88606aa808190aa0b421b4271f220 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90ab5d1a08190a3325ff203b573fb |
completed | March 5, 2026, 4:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad798680088190a24dd968aab1baf0 |
completed | March 8, 2026, 1:28 p.m. |
Created at: March 4, 2026, 7:29 p.m.