Triple
T5615482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giulio Raimondo Mazzarino |
E147466
|
entity |
| Predicate | deathPlace |
P21
|
FINISHED |
| Object | Vincennes |
E138002
|
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: Vincennes | Statement: [Giulio Raimondo Mazzarino, deathPlace, Vincennes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vincennes Context triple: [Giulio Raimondo Mazzarino, deathPlace, Vincennes]
-
A.
Vincennes
chosen
Vincennes is a historic commune just east of Paris, France, known for its medieval Château de Vincennes and long-standing royal connections.
-
B.
Vincennes, Indiana
Vincennes, Indiana is a historic city in southwestern Indiana known as the state’s oldest city and an early frontier settlement along the Wabash River.
-
C.
Lafayette, Indiana
Lafayette, Indiana is a mid-sized city in northwestern Indiana known as a regional economic and educational hub near Purdue University.
-
D.
Lafayette
Lafayette is a mid-sized city in southern Louisiana known as a cultural hub of Cajun and Creole music, food, and festivals.
-
E.
Lafayette
Lafayette was a French aristocrat and military officer who became a key general in the American Revolutionary War and a symbol of Franco-American alliance.
- 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_69c00905d4588190bd967842bbcf2219 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c021d8d600819097df4e265e262d90 |
completed | March 22, 2026, 5:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d51c12c8190911fb9a0c0d234d8 |
completed | March 22, 2026, 8:13 p.m. |
Created at: March 22, 2026, 3:39 p.m.