Triple
T21715256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boissière (Paris Métro) |
E536008
|
entity |
| Predicate | hasBorough |
P300
|
FINISHED |
| Object | Passy district |
—
|
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: Passy district | Statement: [Boissière (Paris Métro), hasBorough, Passy district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Passy district Context triple: [Boissière (Paris Métro), hasBorough, Passy district]
-
A.
Passy
chosen
Passy is a Paris Métro station in the 16th arrondissement, serving Line 6 near the Trocadéro and the Seine.
-
B.
Passy
Passy is a French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region, known for its Alpine setting near Mont Blanc.
-
C.
Balard district
The Balard district is a neighborhood in southwest Paris known for hosting major French defense and aerospace institutions, including the Ministry of the Armed Forces headquarters.
-
D.
Necker district
Necker district is a neighborhood in Paris known for housing major institutions such as the Necker–Enfants Malades Hospital and parts of the Montparnasse area.
-
E.
Belval district
Belval district is a modern urban quarter in Esch-sur-Alzette, Luxembourg, known for its transformation from a former steelworks site into a major hub for education, research, business, and culture.
- 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_69e0c46c6dd88190a595375fa6ebd701 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb53761b48190954a46e8155a84f0 |
completed | April 27, 2026, 7:12 p.m. |
Created at: April 16, 2026, 6:47 p.m.