Triple
T5513068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Zay |
E144612
|
entity |
| Predicate | managedBy |
P86
|
FINISHED |
| Object |
IDRIS
IDRIS is a French national high-performance computing center that provides supercomputing resources and support for scientific research.
|
E534553
|
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: IDRIS | Statement: [Jean Zay, managedBy, IDRIS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IDRIS Context triple: [Jean Zay, managedBy, IDRIS]
-
A.
Idris Alooma
Idris Alooma was a powerful 16th-century ruler of the Bornu Empire known for his military conquests, administrative and Islamic reforms, and expansion of trans-Saharan trade.
-
B.
Idre
Idre is a village and popular outdoor tourism destination in Dalarna County, Sweden, known for its nearby ski resort and mountain landscapes.
-
C.
إدريس
إدريس هو اسم علم عربي يُستخدم للذكور وله جذور دينية وتاريخية في الثقافة الإسلامية.
-
D.
Iddo
Iddo is a biblical figure mentioned in the Old Testament, known primarily as an ancestor of the prophet Zechariah and sometimes identified as a seer or priest.
-
E.
Damson Idris
Damson Idris is a British actor best known for his lead role as Franklin Saint in the crime drama series "Snowfall" and for his work in various film and television projects.
- 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: IDRIS Triple: [Jean Zay, managedBy, IDRIS]
Generated description
IDRIS is a French national high-performance computing center that provides supercomputing resources and support for scientific research.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: IDRIS Target entity description: IDRIS is a French national high-performance computing center that provides supercomputing resources and support for scientific research.
-
A.
Idris Alooma
Idris Alooma was a powerful 16th-century ruler of the Bornu Empire known for his military conquests, administrative and Islamic reforms, and expansion of trans-Saharan trade.
-
B.
Idre
Idre is a village and popular outdoor tourism destination in Dalarna County, Sweden, known for its nearby ski resort and mountain landscapes.
-
C.
إدريس
إدريس هو اسم علم عربي يُستخدم للذكور وله جذور دينية وتاريخية في الثقافة الإسلامية.
-
D.
Iddo
Iddo is a biblical figure mentioned in the Old Testament, known primarily as an ancestor of the prophet Zechariah and sometimes identified as a seer or priest.
-
E.
Damson Idris
Damson Idris is a British actor best known for his lead role as Franklin Saint in the crime drama series "Snowfall" and for his work in various film and television projects.
- 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_69c008f77ff88190b0cd50ca207295d1 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f599d0881909ce86fcc45d4d920 |
completed | March 22, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04cc0735881909b7ea6909570a750 |
completed | March 22, 2026, 8:10 p.m. |
| NEDg | Description generation | batch_69c04e827bdc819086e01e7043400452 |
completed | March 22, 2026, 8:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c04f088a3c81909610f1a564960e0f |
completed | March 22, 2026, 8:20 p.m. |
Created at: March 22, 2026, 3:33 p.m.