Triple
T7281588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aziz Sancar |
E163161
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Sancar
Sancar is the surname of Aziz Sancar, a Turkish-American biochemist and molecular biologist renowned for his Nobel Prize–winning work on DNA repair.
|
E654087
|
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: Sancar | Statement: [Aziz Sancar, familyName, Sancar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sancar Context triple: [Aziz Sancar, familyName, Sancar]
-
A.
Sokar
Sokar is an ancient Egyptian funerary god associated with the Memphite necropolis, the afterlife, and aspects of death and rebirth.
-
B.
Sardoal
Sardoal is a small Portuguese municipality known for its historic village center and traditional religious and cultural festivities, located in the Centro Region of Portugal.
-
C.
Sagala
Sagala was an important ancient city in the Punjab region, historically known as a major political and cultural center under Indo-Greek rule.
-
D.
Sanchica
Sanchica is the fictional daughter of Sancho Panza in Miguel de Cervantes' novel "Don Quixote."
-
E.
Sanaig
Sanaig is a core single malt Scotch whisky expression from Islay’s Kilchoman distillery, known for its balance of bourbon and sherry cask influence with a characteristically smoky, coastal profile.
- 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: Sancar Triple: [Aziz Sancar, familyName, Sancar]
Generated description
Sancar is the surname of Aziz Sancar, a Turkish-American biochemist and molecular biologist renowned for his Nobel Prize–winning work on DNA repair.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sancar Target entity description: Sancar is the surname of Aziz Sancar, a Turkish-American biochemist and molecular biologist renowned for his Nobel Prize–winning work on DNA repair.
-
A.
Sokar
Sokar is an ancient Egyptian funerary god associated with the Memphite necropolis, the afterlife, and aspects of death and rebirth.
-
B.
Sardoal
Sardoal is a small Portuguese municipality known for its historic village center and traditional religious and cultural festivities, located in the Centro Region of Portugal.
-
C.
Sagala
Sagala was an important ancient city in the Punjab region, historically known as a major political and cultural center under Indo-Greek rule.
-
D.
Sanchica
Sanchica is the fictional daughter of Sancho Panza in Miguel de Cervantes' novel "Don Quixote."
-
E.
Sanaig
Sanaig is a core single malt Scotch whisky expression from Islay’s Kilchoman distillery, known for its balance of bourbon and sherry cask influence with a characteristically smoky, coastal profile.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb34fe0c8190a642fd3339f0cacd |
completed | March 27, 2026, 8:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db379e1c81908ebd4c44504ce5fb |
completed | March 28, 2026, 1:44 p.m. |
| NEDg | Description generation | batch_69c7df4788e081908ccc162125c6550d |
completed | March 28, 2026, 2:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7dfa826d081909129df80cca13daa |
completed | March 28, 2026, 2:03 p.m. |
Created at: March 27, 2026, 2:59 p.m.