Triple
T13960514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMND |
E335778
|
entity |
| Predicate | hasPartInName |
P5298
|
FINISHED |
| Object | Saint-Michel |
E207643
|
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: Saint-Michel | Statement: [SMND, hasPartInName, Saint-Michel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Michel Context triple: [SMND, hasPartInName, Saint-Michel]
-
A.
Saint-Michel
chosen
Saint-Michel is a central Paris Métro station on the Left Bank, serving the busy Saint-Michel–Notre-Dame area near the Seine and key historic landmarks.
-
B.
Saint-Michel
Saint-Michel is a Montreal Metro station that serves as the eastern terminus of the Blue Line in Montreal, Quebec, Canada.
-
C.
Saint-Paul-Saint-Louis
Saint-Paul-Saint-Louis is a historic 17th-century Roman Catholic church in Paris’s Marais district, noted for its Baroque architecture and richly decorated interior.
-
D.
Saint-Denis-du-Port
Saint-Denis-du-Port is a locality in France historically noted as the place where the 18th-century French painter and etcher Jean-Baptiste Le Prince died.
-
E.
Saint-Ambroise
Saint-Ambroise is a small municipality in the Saguenay–Lac-Saint-Jean region of Quebec, Canada, known for its agricultural character and rural setting.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7b2f908190aa32f22298964746 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc321c600819085052392de9b0b53 |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:17 p.m.