Triple
T22768856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronald Searle |
E563197
|
entity |
| Predicate | workedFor |
P1910
|
FINISHED |
| Object | Le Monde |
—
|
NE NERFINISHED |
How this triple was built (2 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: Le Monde | Statement: [Ronald Searle, workedFor, Le Monde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Monde Context triple: [Ronald Searle, workedFor, Le Monde]
-
A.
Le Monde
chosen
Le Monde is a leading French daily newspaper known for its in-depth political, cultural, and international reporting.
-
B.
France-Soir
France-Soir is a French daily newspaper that became one of the country’s most widely read popular papers in the mid-20th century.
-
C.
Le Figaro
Le Figaro is one of France’s oldest and most influential daily newspapers, known for its conservative editorial stance and major role in the country’s cultural and political life.
-
D.
La Presse
La Presse is a prominent French-language newspaper historically known for serializing major literary works and influencing public opinion in France.
-
E.
Le Matin
Le Matin is a prominent French daily newspaper that was especially influential in the late 19th and early 20th centuries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b59c9cc8190a6edd68f3209a672 |
completed | April 29, 2026, 3:30 a.m. |
Created at: April 17, 2026, 3:27 p.m.