Triple
T22204731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Exelmans |
E548774
|
entity |
| Predicate | adjacentStationOnLine9 |
P83323
|
FINISHED |
| Object | Michel-Ange–Molitor |
—
|
NE NERFINISHED |
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: Michel-Ange–Molitor | Statement: [Exelmans, adjacentStationOnLine9, Michel-Ange–Molitor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michel-Ange–Molitor Context triple: [Exelmans, adjacentStationOnLine9, Michel-Ange–Molitor]
-
A.
Michel-Ange–Molitor
chosen
Michel-Ange–Molitor is a Paris Métro station in the 16th arrondissement that serves as an interchange between lines 9 and 10.
-
B.
Fantin-Latour
Fantin-Latour was a French painter and lithographer renowned for his delicate flower still lifes and intimate group portraits of 19th-century artists.
-
C.
Michel-Ange–Auteuil
Michel-Ange–Auteuil is a Paris Métro station in the 16th arrondissement, serving as an interchange between lines 9 and 10.
-
D.
Michel
Michel is a fictional character appearing in Frederick Forsyth’s political thriller novel "The Dogs of War."
-
E.
Michel
Michel is the birth name of the acclaimed Egyptian actor Omar Sharif, renowned for his roles in classic films such as "Lawrence of Arabia" and "Doctor Zhivago."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b27451081908c29d1915b6c4229 |
completed | April 28, 2026, 9:48 p.m. |
Created at: April 16, 2026, 8:36 p.m.