Triple
T6860132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nido R. Qubein |
E158253
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Nido
Nido is the given name of Nido R. Qubein, a business leader, motivational speaker, and president of High Point University.
|
E624569
|
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: Nido | Statement: [Nido R. Qubein, givenName, Nido]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nido Context triple: [Nido R. Qubein, givenName, Nido]
-
A.
Pichu Pichu
Pichu Pichu is a large, eroded volcanic massif in southern Peru, known for its multiple peaks and cultural significance near the city of Arequipa.
-
B.
Lapus Lapus
Lapus Lapus is a popular scuba diving site off Malapascua Island in the Philippines, known for its vibrant coral reefs and diverse marine life.
-
C.
Nursino
Nursino is the Italian demonym for a person originating from the town of Nursia (Norcia) in Umbria, Italy.
-
D.
Quatchi
Quatchi is a sasquatch character who served as one of the official mascots of the 2010 Winter Olympics in Vancouver.
-
E.
Pioppi
Pioppi is a small coastal village in southern Italy’s Cilento region, known for its traditional Mediterranean lifestyle and as a key site in the study of the Mediterranean diet.
- 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: Nido Triple: [Nido R. Qubein, givenName, Nido]
Generated description
Nido is the given name of Nido R. Qubein, a business leader, motivational speaker, and president of High Point University.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nido Target entity description: Nido is the given name of Nido R. Qubein, a business leader, motivational speaker, and president of High Point University.
-
A.
Pichu Pichu
Pichu Pichu is a large, eroded volcanic massif in southern Peru, known for its multiple peaks and cultural significance near the city of Arequipa.
-
B.
Lapus Lapus
Lapus Lapus is a popular scuba diving site off Malapascua Island in the Philippines, known for its vibrant coral reefs and diverse marine life.
-
C.
Nursino
Nursino is the Italian demonym for a person originating from the town of Nursia (Norcia) in Umbria, Italy.
-
D.
Quatchi
Quatchi is a sasquatch character who served as one of the official mascots of the 2010 Winter Olympics in Vancouver.
-
E.
Pioppi
Pioppi is a small coastal village in southern Italy’s Cilento region, known for its traditional Mediterranean lifestyle and as a key site in the study of the Mediterranean diet.
- 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_69c68830cdbc8190a8301c7a9d9f651a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8737fac81909fc546ca2bf6a278 |
completed | March 27, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72fe79af081909baacbfd4d5e8f24 |
completed | March 28, 2026, 1:33 a.m. |
| NEDg | Description generation | batch_69c7399b95e081908bbee3a598d6513c |
completed | March 28, 2026, 2:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c739f1b20c8190a8ef57357d4956b4 |
completed | March 28, 2026, 2:16 a.m. |
Created at: March 27, 2026, 2:21 p.m.