Triple
T12240545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jérôme Coumet |
E291716
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Coumet
Coumet is a French surname most notably borne by Jérôme Coumet, a contemporary French politician.
|
E970986
|
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: Coumet | Statement: [Jérôme Coumet, familyName, Coumet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coumet Context triple: [Jérôme Coumet, familyName, Coumet]
-
A.
Arkema
Arkema is a French multinational specialty chemicals and advanced materials company known for its innovations in adhesives, coatings, and performance polymers.
-
B.
Dupont
Dupont is a common French surname shared by various notable individuals across fields such as politics, arts, and sports.
-
C.
Rhodia
Rhodia is a fictional alien planet in the Doctor Who universe, known primarily as the homeworld of the character Miss Quill from the spin-off series "Class."
-
D.
Chamical
Chamical is a small city in central La Rioja Province, Argentina, known historically as a regional railway and agricultural center.
-
E.
Dampierre
Dampierre is a small French commune located in the Aube department in the Grand Est region of north-central France.
- 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: Coumet Triple: [Jérôme Coumet, familyName, Coumet]
Generated description
Coumet is a French surname most notably borne by Jérôme Coumet, a contemporary French politician.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Coumet Target entity description: Coumet is a French surname most notably borne by Jérôme Coumet, a contemporary French politician.
-
A.
Arkema
Arkema is a French multinational specialty chemicals and advanced materials company known for its innovations in adhesives, coatings, and performance polymers.
-
B.
Dupont
Dupont is a common French surname shared by various notable individuals across fields such as politics, arts, and sports.
-
C.
Rhodia
Rhodia is a fictional alien planet in the Doctor Who universe, known primarily as the homeworld of the character Miss Quill from the spin-off series "Class."
-
D.
Chamical
Chamical is a small city in central La Rioja Province, Argentina, known historically as a regional railway and agricultural center.
-
E.
Dampierre
Dampierre is a small French commune located in the Aube department in the Grand Est region of north-central France.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cb59ce4819099999b8755fb8b98 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60ab3ae2481908f65d8ac61a6b2e4 |
completed | May 2, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69f60bdd8d508190813178ff4c77afcf |
completed | May 2, 2026, 2:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60c67c680819087630d190d0a008f |
completed | May 2, 2026, 2:38 p.m. |
Created at: April 8, 2026, 9:51 p.m.