Triple
T12592277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | arrondissement of Saint-Germain-en-Laye |
E300634
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Médan
Médan is a small commune in north-central France, known for its picturesque setting along the Seine and its association with the writer Émile Zola.
|
E993860
|
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: Médan | Statement: [arrondissement of Saint-Germain-en-Laye, contains, Médan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Médan Context triple: [arrondissement of Saint-Germain-en-Laye, contains, Médan]
-
A.
Tuapse
Tuapse is a Black Sea port town in southern Russia known as a seaside resort and industrial center within Krasnodar Krai.
-
B.
Cherepovets
Cherepovets is a major industrial city in northwestern Russia, known especially for its large steel production and chemical industries.
-
C.
Nikolaev
Nikolaev is the Russian-language name for Mykolaiv, a major shipbuilding and industrial city in southern Ukraine located near the Black Sea.
-
D.
Soligorsk
Soligorsk is an industrial city in Belarus known for its large potash mining operations and location in the southern part of the Minsk Region.
-
E.
Sestroretsk
Sestroretsk is a town in northwestern Russia, now part of Saint Petersburg, historically known for its arms factory and seaside resort area on the Gulf of Finland.
- 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: Médan Triple: [arrondissement of Saint-Germain-en-Laye, contains, Médan]
Generated description
Médan is a small commune in north-central France, known for its picturesque setting along the Seine and its association with the writer Émile Zola.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Médan Target entity description: Médan is a small commune in north-central France, known for its picturesque setting along the Seine and its association with the writer Émile Zola.
-
A.
Tuapse
Tuapse is a Black Sea port town in southern Russia known as a seaside resort and industrial center within Krasnodar Krai.
-
B.
Cherepovets
Cherepovets is a major industrial city in northwestern Russia, known especially for its large steel production and chemical industries.
-
C.
Nikolaev
Nikolaev is the Russian-language name for Mykolaiv, a major shipbuilding and industrial city in southern Ukraine located near the Black Sea.
-
D.
Soligorsk
Soligorsk is an industrial city in Belarus known for its large potash mining operations and location in the southern part of the Minsk Region.
-
E.
Sestroretsk
Sestroretsk is a town in northwestern Russia, now part of Saint Petersburg, historically known for its arms factory and seaside resort area on the Gulf of Finland.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954cc6d3c81908fbb22601c46f3f7 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ec2dac88190bf31bb00f93feb30 |
completed | May 2, 2026, 8:29 p.m. |
| NEDg | Description generation | batch_69f66308087c81908ab5b5795f255e37 |
completed | May 2, 2026, 8:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f663fe2fac8190bb70c8f1b919d657 |
completed | May 2, 2026, 8:52 p.m. |
Created at: April 9, 2026, 5:07 p.m.