Triple
T3200666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandra Lee |
E67041
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Christiansen
Christiansen is a surname of Scandinavian origin borne by various individuals, including American television chef and author Sandra Lee.
|
E336474
|
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: Christiansen | Statement: [Sandra Lee, familyName, Christiansen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christiansen Context triple: [Sandra Lee, familyName, Christiansen]
-
A.
Christian Christiansen
Christian Christiansen was a Danish physicist and professor known for his work in optics and thermodynamics and for mentoring notable scientists, including Niels Bohr.
-
B.
Karlssen
Karlssen is a Scandinavian-origin surname, likely a patronymic variant related to the more common name Carlson.
-
C.
Robertsen
Robertsen is a surname of likely Scandinavian origin, functioning as a patronymic variant of the name Roberts.
-
D.
Martinsen
Martinsen is a Scandinavian patronymic surname meaning "son of Martin," related to the Spanish surname Martinez.
-
E.
Kristian Kristiansen
Kristian Kristiansen is an adventurer known for participating in an expedition that crossed the Greenland ice cap.
- 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: Christiansen Triple: [Sandra Lee, familyName, Christiansen]
Generated description
Christiansen is a surname of Scandinavian origin borne by various individuals, including American television chef and author Sandra Lee.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Christiansen Target entity description: Christiansen is a surname of Scandinavian origin borne by various individuals, including American television chef and author Sandra Lee.
-
A.
Christian Christiansen
Christian Christiansen was a Danish physicist and professor known for his work in optics and thermodynamics and for mentoring notable scientists, including Niels Bohr.
-
B.
Karlssen
Karlssen is a Scandinavian-origin surname, likely a patronymic variant related to the more common name Carlson.
-
C.
Robertsen
Robertsen is a surname of likely Scandinavian origin, functioning as a patronymic variant of the name Roberts.
-
D.
Martinsen
Martinsen is a Scandinavian patronymic surname meaning "son of Martin," related to the Spanish surname Martinez.
-
E.
Kristian Kristiansen
Kristian Kristiansen is an adventurer known for participating in an expedition that crossed the Greenland ice cap.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9aedef08190824bdf508f85f06f |
completed | March 8, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24bc3695c8190abd58dbc74ca2271 |
completed | March 12, 2026, 5:14 a.m. |
| NEDg | Description generation | batch_69b24d677ca8819094cb03360ac885da |
completed | March 12, 2026, 5:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2517e2afc8190a6f8dfa66d3671d5 |
completed | March 12, 2026, 5:39 a.m. |
Created at: March 8, 2026, 3:07 p.m.