Triple
T6616858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lagardère Group |
E149373
|
entity |
| Predicate | owns |
P347
|
FINISHED |
| Object |
Grasset
Grasset is a prominent French publishing house known for its literary fiction and non-fiction catalog.
|
E599870
|
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: Grasset | Statement: [Lagardère Group, owns, Grasset]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grasset Context triple: [Lagardère Group, owns, Grasset]
-
A.
Brévent
Brévent is a prominent mountain and viewpoint in the French Alps overlooking the Chamonix valley and offering panoramic views of the Mont Blanc massif.
-
B.
Le Barcarès
Le Barcarès is a coastal commune in southern France on the Mediterranean Sea, known for its beaches, marina, and tourism.
-
C.
Le Gosier
Le Gosier is a coastal commune and popular tourist resort town on the island of Grande-Terre in Guadeloupe, known for its beaches, marinas, and vibrant nightlife.
-
D.
Brévands
Brévands is a former commune in the Manche department of northwestern France, now part of the larger municipality of Carentan-les-Marais.
-
E.
Le Roeulx
Le Roeulx is a historic town in the province of Hainaut in Wallonia, Belgium, known for its castle, traditional architecture, and proximity to the Canal du Centre.
- 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: Grasset Triple: [Lagardère Group, owns, Grasset]
Generated description
Grasset is a prominent French publishing house known for its literary fiction and non-fiction catalog.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grasset Target entity description: Grasset is a prominent French publishing house known for its literary fiction and non-fiction catalog.
-
A.
Brévent
Brévent is a prominent mountain and viewpoint in the French Alps overlooking the Chamonix valley and offering panoramic views of the Mont Blanc massif.
-
B.
Le Barcarès
Le Barcarès is a coastal commune in southern France on the Mediterranean Sea, known for its beaches, marina, and tourism.
-
C.
Le Gosier
Le Gosier is a coastal commune and popular tourist resort town on the island of Grande-Terre in Guadeloupe, known for its beaches, marinas, and vibrant nightlife.
-
D.
Brévands
Brévands is a former commune in the Manche department of northwestern France, now part of the larger municipality of Carentan-les-Marais.
-
E.
Le Roeulx
Le Roeulx is a historic town in the province of Hainaut in Wallonia, Belgium, known for its castle, traditional architecture, and proximity to the Canal du Centre.
- 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_69c687ebc680819094caf71faba2efe2 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af59a344819089ec755296f04381 |
completed | March 27, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbda469481908173db345ba2f216 |
completed | March 27, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69c6cd428b988190b01311ca02f4dff3 |
completed | March 27, 2026, 6:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6cdcc10c08190aa98212bd17063a3 |
completed | March 27, 2026, 6:34 p.m. |
Created at: March 27, 2026, 1:57 p.m.