Triple
T14350800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Michels station |
E355845
|
entity |
| Predicate | servesNeighborhood |
P82
|
FINISHED |
| Object | Beaugrenelle |
E548832
|
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: Beaugrenelle | Statement: [Charles Michels station, servesNeighborhood, Beaugrenelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beaugrenelle Context triple: [Charles Michels station, servesNeighborhood, Beaugrenelle]
-
A.
Beaugrenelle
chosen
Beaugrenelle is a modern riverside district in Paris known for its high-rise architecture, shopping center, and contemporary urban design along the Seine.
-
B.
Marolles
Marolles is a historic working-class neighborhood in central Brussels known for its vibrant flea market, antique shops, and lively street culture.
-
C.
Daumesnil
Daumesnil is a Paris Métro station located in the 12th arrondissement, serving as an interchange between lines 6 and 8 near Place Félix-Éboué.
-
D.
Étrépilly
Étrépilly is a small French commune located in the Seine-et-Marne department in the Île-de-France region in north-central France.
-
E.
Goutte d'Or
Goutte d'Or is a vibrant, historically working-class neighborhood in Paris known for its diverse immigrant communities, bustling markets, and rich North and West African cultural influences.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f4e1e588190bdc7aaf7a2819948 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5be63848190aa71f009ceaea1b3 |
completed | May 8, 2026, 12:23 p.m. |
Created at: April 10, 2026, 1:14 a.m.