Triple
T5456044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Théâtre Feydeau |
E122480
|
entity |
| Predicate | locatedOn |
P40
|
FINISHED |
| Object |
Rue Feydeau
Rue Feydeau is a street in central Paris, France, historically notable for hosting the prominent Théâtre Feydeau.
|
E666031
|
NE FINISHED |
How this triple was built (4 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: Rue Feydeau | Statement: [Théâtre Feydeau, locatedOn, Rue Feydeau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rue Feydeau Context triple: [Théâtre Feydeau, locatedOn, Rue Feydeau]
-
A.
Rue Pierre-Dupuy
Rue Pierre-Dupuy is a street located on the Cité du Havre peninsula in Montreal, known for serving the residential and recreational areas along the Saint Lawrence River waterfront.
-
B.
Rue Santeuil
Rue Santeuil is a street in Nantes, France, known for hosting the historic Passage Pommeraye shopping arcade.
-
C.
Rue Belliard
Rue Belliard is a major street in Brussels’ European Quarter, lined with EU institutions, offices, and diplomatic buildings.
-
D.
Rue Lepic
Rue Lepic is a historic, winding street in Paris’s Montmartre district, known for its cafés, artistic heritage, and views over the city.
-
E.
Rue Malher
Rue Malher is a street in the historic Marais district of Paris, France, known for its proximity to notable sites including the former La Force prison.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rue Feydeau Triple: [Théâtre Feydeau, locatedOn, Rue Feydeau]
Generated description
Rue Feydeau is a street in central Paris, France, historically notable for hosting the prominent Théâtre Feydeau.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rue Feydeau Target entity description: Rue Feydeau is a street in central Paris, France, historically notable for hosting the prominent Théâtre Feydeau.
-
A.
Rue Pierre-Dupuy
Rue Pierre-Dupuy is a street located on the Cité du Havre peninsula in Montreal, known for serving the residential and recreational areas along the Saint Lawrence River waterfront.
-
B.
Rue Santeuil
Rue Santeuil is a street in Nantes, France, known for hosting the historic Passage Pommeraye shopping arcade.
-
C.
Rue Belliard
Rue Belliard is a major street in Brussels’ European Quarter, lined with EU institutions, offices, and diplomatic buildings.
-
D.
Rue Lepic
Rue Lepic is a historic, winding street in Paris’s Montmartre district, known for its cafés, artistic heritage, and views over the city.
-
E.
Rue Malher
Rue Malher is a street in the historic Marais district of Paris, France, known for its proximity to notable sites including the former La Force prison.
- F. None of above. chosen
Provenance (5 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd91eeb7ac8190bf2e02f7946bf2bf |
completed | March 20, 2026, 6:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83414c374819085ca1e441728c6af |
completed | March 28, 2026, 8:03 p.m. |
| NEDg | Description generation | batch_69c834df98908190a13df51182751a75 |
completed | March 28, 2026, 8:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c83597d0f0819091a095e8376fd644 |
completed | March 28, 2026, 8:10 p.m. |
Created at: March 20, 2026, 2:08 p.m.