Triple
T13693523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre Savoye |
E328326
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object |
L’Union
L’Union is a French regional newspaper known for covering local and national news in the Champagne-Ardenne and surrounding areas.
|
E1054353
|
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: L’Union | Statement: [Pierre Savoye, employer, L’Union]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: L’Union Context triple: [Pierre Savoye, employer, L’Union]
-
A.
La Union
La Union is a coastal province in the Ilocos Region of the Philippines known for its Ilocano heritage, surfing beaches, and emerging tourism industry.
-
B.
French Union
The French Union was a political entity established after World War II to reorganize France’s relationship with its colonies and overseas territories within a quasi-federal framework.
-
C.
Francie
Francie is a diminutive given name, typically used as a nickname for Francis or Frances.
-
D.
Arpitanie
Arpitanie is a cultural and linguistic region in parts of France, Switzerland, and Italy where the Arpitan (Franco-Provençal) language and related traditions are historically rooted.
-
E.
Libé
Libé is the common nickname for Libération, a prominent French daily newspaper known for its left-leaning, progressive editorial stance.
- 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: L’Union Triple: [Pierre Savoye, employer, L’Union]
Generated description
L’Union is a French regional newspaper known for covering local and national news in the Champagne-Ardenne and surrounding areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: L’Union Target entity description: L’Union is a French regional newspaper known for covering local and national news in the Champagne-Ardenne and surrounding areas.
-
A.
La Union
La Union is a coastal province in the Ilocos Region of the Philippines known for its Ilocano heritage, surfing beaches, and emerging tourism industry.
-
B.
French Union
The French Union was a political entity established after World War II to reorganize France’s relationship with its colonies and overseas territories within a quasi-federal framework.
-
C.
Francie
Francie is a diminutive given name, typically used as a nickname for Francis or Frances.
-
D.
Arpitanie
Arpitanie is a cultural and linguistic region in parts of France, Switzerland, and Italy where the Arpitan (Franco-Provençal) language and related traditions are historically rooted.
-
E.
Libé
Libé is the common nickname for Libération, a prominent French daily newspaper known for its left-leaning, progressive editorial stance.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8757b648190a26181efbad09a43 |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7944e7ea0819098a9fbf8842d314b |
completed | May 3, 2026, 6:30 p.m. |
| NEDg | Description generation | batch_69f79715571081909c1177a3fd09b4d5 |
completed | May 3, 2026, 6:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f797caabfc8190844e6b7d8125aeb6 |
completed | May 3, 2026, 6:45 p.m. |
Created at: April 9, 2026, 9:54 p.m.