Triple
T15308614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Havre urban area |
E365969
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Beaurepaire
Beaurepaire is a locality within the Le Havre metropolitan area in northern France, integrated into its broader urban and residential landscape.
|
E1149593
|
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: Beaurepaire | Statement: [Le Havre urban area, hasPart, Beaurepaire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beaurepaire Context triple: [Le Havre urban area, hasPart, Beaurepaire]
-
A.
Beaugrenelle
Beaugrenelle is a modern riverside district in Paris known for its high-rise architecture, shopping center, and contemporary urban design along the Seine.
-
B.
Boucicaut
Boucicaut is a station on the Paris Métro serving the 15th arrondissement of Paris.
-
C.
Marolles
Marolles is a historic working-class neighborhood in central Brussels known for its vibrant flea market, antique shops, and lively street culture.
-
D.
Beauseant
Beauseant is a scheming aristocrat and one of the principal antagonists in Edward Bulwer-Lytton’s romantic drama "The Lady of Lyons."
-
E.
Noailles
Noailles is a renowned art district in Croix-des-Bouquets, Haiti, famous for its vibrant community of metal sculptors and artisans.
- 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: Beaurepaire Triple: [Le Havre urban area, hasPart, Beaurepaire]
Generated description
Beaurepaire is a locality within the Le Havre metropolitan area in northern France, integrated into its broader urban and residential landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beaurepaire Target entity description: Beaurepaire is a locality within the Le Havre metropolitan area in northern France, integrated into its broader urban and residential landscape.
-
A.
Beaugrenelle
Beaugrenelle is a modern riverside district in Paris known for its high-rise architecture, shopping center, and contemporary urban design along the Seine.
-
B.
Boucicaut
Boucicaut is a station on the Paris Métro serving the 15th arrondissement of Paris.
-
C.
Marolles
Marolles is a historic working-class neighborhood in central Brussels known for its vibrant flea market, antique shops, and lively street culture.
-
D.
Beauseant
Beauseant is a scheming aristocrat and one of the principal antagonists in Edward Bulwer-Lytton’s romantic drama "The Lady of Lyons."
-
E.
Noailles
Noailles is a renowned art district in Croix-des-Bouquets, Haiti, famous for its vibrant community of metal sculptors and artisans.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03cd001b48190bbdd69337efdb907 |
completed | April 16, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef89feda88190b18f6a03d6e968aa |
completed | May 9, 2026, 9:04 a.m. |
| NEDg | Description generation | batch_69fefa13e8508190930a22439b7f154a |
completed | May 9, 2026, 9:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fefa80be14819089e87e7bdb3af7ec |
completed | May 9, 2026, 9:12 a.m. |
Created at: April 10, 2026, 3:16 a.m.