Triple
T14834195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claude Lantier |
E348785
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Lantier
Lantier is a French surname most notably associated with Claude Lantier, a fictional painter in Émile Zola’s Rougon-Macquart novel cycle.
|
E1122099
|
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: Lantier | Statement: [Claude Lantier, familyName, Lantier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lantier Context triple: [Claude Lantier, familyName, Lantier]
-
A.
Lazzeri
Lazzeri is an Italian surname most famously associated with Hall of Fame baseball player Tony Lazzeri.
-
B.
Lisberg
Lisberg is a Danish-origin surname most notably associated with figures such as Jens Oliver Lisberg.
-
C.
Faventia
Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
-
D.
Riva
Riva is a coastal neighborhood and popular recreational area on the Asian side of Istanbul, known for its beaches, river, and natural scenery.
-
E.
Sintermaris
Sintermaris is an alternative historical or Latin name for the French town of Saint-Omer in the Pas-de-Calais region.
- 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: Lantier Triple: [Claude Lantier, familyName, Lantier]
Generated description
Lantier is a French surname most notably associated with Claude Lantier, a fictional painter in Émile Zola’s Rougon-Macquart novel cycle.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lantier Target entity description: Lantier is a French surname most notably associated with Claude Lantier, a fictional painter in Émile Zola’s Rougon-Macquart novel cycle.
-
A.
Lazzeri
Lazzeri is an Italian surname most famously associated with Hall of Fame baseball player Tony Lazzeri.
-
B.
Lisberg
Lisberg is a Danish-origin surname most notably associated with figures such as Jens Oliver Lisberg.
-
C.
Faventia
Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
-
D.
Riva
Riva is a coastal neighborhood and popular recreational area on the Asian side of Istanbul, known for its beaches, river, and natural scenery.
-
E.
Sintermaris
Sintermaris is an alternative historical or Latin name for the French town of Saint-Omer in the Pas-de-Calais region.
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded075af0881908fb35a9e7ee46749 |
completed | April 14, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe38a5d8888190821988ad00351d05 |
completed | May 8, 2026, 7:25 p.m. |
| NEDg | Description generation | batch_69fe3c99aae48190be6a4bd5914217f3 |
completed | May 8, 2026, 7:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe3d0122bc8190baa8c694ade8cc26 |
completed | May 8, 2026, 7:44 p.m. |
Created at: April 10, 2026, 1:52 a.m.