Triple
T16484368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orano |
E400399
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object |
Orano Med
Orano Med is a nuclear medicine company specializing in the development of targeted alpha therapies for cancer treatment.
|
E1217030
|
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: Orano Med | Statement: [Orano, hasSubsidiary, Orano Med]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orano Med Context triple: [Orano, hasSubsidiary, Orano Med]
-
A.
Orano
Orano is a French multinational nuclear fuel cycle company specializing in uranium mining, conversion, enrichment, recycling, and related nuclear services.
-
B.
Orano Melox plant
The Orano Melox plant is a French nuclear fuel fabrication facility that produces mixed oxide (MOX) fuel for use in nuclear power reactors.
-
C.
Sogea-Satom
Sogea-Satom is a construction and civil engineering company operating primarily in Africa, specializing in infrastructure projects such as roads, bridges, and public works.
-
D.
Nucourt
Nucourt is a small commune in the Val-d'Oise department in the Île-de-France region of northern France.
-
E.
Durolle
Durolle is a river in central France that flows through the town of Thiers, historically powering its renowned cutlery and knife-making industry.
- 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: Orano Med Triple: [Orano, hasSubsidiary, Orano Med]
Generated description
Orano Med is a nuclear medicine company specializing in the development of targeted alpha therapies for cancer treatment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Orano Med Target entity description: Orano Med is a nuclear medicine company specializing in the development of targeted alpha therapies for cancer treatment.
-
A.
Orano
Orano is a French multinational nuclear fuel cycle company specializing in uranium mining, conversion, enrichment, recycling, and related nuclear services.
-
B.
Orano Melox plant
The Orano Melox plant is a French nuclear fuel fabrication facility that produces mixed oxide (MOX) fuel for use in nuclear power reactors.
-
C.
Sogea-Satom
Sogea-Satom is a construction and civil engineering company operating primarily in Africa, specializing in infrastructure projects such as roads, bridges, and public works.
-
D.
Nucourt
Nucourt is a small commune in the Val-d'Oise department in the Île-de-France region of northern France.
-
E.
Durolle
Durolle is a river in central France that flows through the town of Thiers, historically powering its renowned cutlery and knife-making industry.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e05bf448190947b9da15fd29d0a |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a005820790c819088d953eeea09328d |
completed | May 10, 2026, 10:04 a.m. |
| NEDg | Description generation | batch_6a0059126e588190b531c145f3c155b4 |
completed | May 10, 2026, 10:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0059b5a1f8819089caefc121246739 |
completed | May 10, 2026, 10:11 a.m. |
Created at: April 10, 2026, 5:13 a.m.