Triple
T268549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christine Teigen |
E5573
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Christine Teigen |
E1036
|
NE FINISHED |
How this triple was built (2 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: Christine Teigen | Statement: [Christine Teigen, name, Christine Teigen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christine Teigen Context triple: [Christine Teigen, name, Christine Teigen]
-
A.
Chrissy Teigen
chosen
Chrissy Teigen is an American model, television personality, and cookbook author known for her Sports Illustrated work, outspoken social media presence, and lifestyle brand.
-
B.
Rachel Ray
"Rachel Ray" is a 19th-century novel by Anthony Trollope that explores themes of love, religious influence, and social pressure in a small English town.
-
C.
Daniel Patterson
Daniel Patterson was the first husband of Mary Baker Eddy, the founder of Christian Science.
-
D.
Nancy Carlson
Nancy Carlson is known as the wife of World Wide Web inventor Sir Tim Berners-Lee.
-
E.
Fannie Farmer
Fannie Farmer was an influential American cook and author whose 1896 "Boston Cooking-School Cook Book" helped standardize modern recipe measurements and home cooking practices.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dae4a0c8190a66cf6ed3889851c |
completed | Feb. 28, 2026, 3:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a38b9082b8819099cd5e7fe3c7335f |
completed | March 1, 2026, 12:42 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.