Triple
T7655555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | École des Mines de Paris |
E173369
|
entity |
| Predicate | notableAlumni |
P51
|
FINISHED |
| Object |
Patrick Kron
Patrick Kron is a French industrialist best known for serving as CEO and later chairman of the engineering and energy group Alstom.
|
E680161
|
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: Patrick Kron | Statement: [École des Mines de Paris, notableAlumni, Patrick Kron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Patrick Kron Context triple: [École des Mines de Paris, notableAlumni, Patrick Kron]
-
A.
Joe Klotz
Joe Klotz is an American film editor best known for his acclaimed work on the drama film "Precious."
-
B.
Paul Rickolt
Paul Rickolt is a music industry figure best known as the founder of the influential American record label Elektra Records.
-
C.
Nick Wasicsko
Nick Wasicsko was a young Yonkers, New York mayor known for his pivotal and contentious role in implementing federally mandated public housing desegregation in the late 1980s.
-
D.
John Kruger
John Kruger is the tough, resourceful U.S. Marshal protagonist in the 1996 action film "Eraser," portrayed by Arnold Schwarzenegger.
-
E.
Greg Beeman
Greg Beeman is an American television director and producer known for his work on genre series such as "Falling Skies," "Heroes," and "Smallville."
- 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: Patrick Kron Triple: [École des Mines de Paris, notableAlumni, Patrick Kron]
Generated description
Patrick Kron is a French industrialist best known for serving as CEO and later chairman of the engineering and energy group Alstom.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Patrick Kron Target entity description: Patrick Kron is a French industrialist best known for serving as CEO and later chairman of the engineering and energy group Alstom.
-
A.
Joe Klotz
Joe Klotz is an American film editor best known for his acclaimed work on the drama film "Precious."
-
B.
Paul Rickolt
Paul Rickolt is a music industry figure best known as the founder of the influential American record label Elektra Records.
-
C.
Nick Wasicsko
Nick Wasicsko was a young Yonkers, New York mayor known for his pivotal and contentious role in implementing federally mandated public housing desegregation in the late 1980s.
-
D.
John Kruger
John Kruger is the tough, resourceful U.S. Marshal protagonist in the 1996 action film "Eraser," portrayed by Arnold Schwarzenegger.
-
E.
Greg Beeman
Greg Beeman is an American television director and producer known for his work on genre series such as "Falling Skies," "Heroes," and "Smallville."
- 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_69c6995473348190a4f41d110d619a18 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7018ea3688190907c3ac7d25e3da6 |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89afd1438819080c8f097df1d1453 |
completed | March 29, 2026, 3:22 a.m. |
| NEDg | Description generation | batch_69c89ec399708190bce316010799298e |
completed | March 29, 2026, 3:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c89f23221c81909efe8596333b7f1c |
completed | March 29, 2026, 3:40 a.m. |
Created at: March 27, 2026, 3:59 p.m.