Triple
T7244480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N. C. Wyeth |
E156438
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wyeth |
E474926
|
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: Wyeth | Statement: [N. C. Wyeth, familyName, Wyeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wyeth Context triple: [N. C. Wyeth, familyName, Wyeth]
-
A.
Wyeth
chosen
Wyeth was a major American pharmaceutical and biotechnology company known for developing vaccines, prescription drugs, and consumer healthcare products before being acquired by Pfizer.
-
B.
Kensett
Kensett is the surname of John Frederick Kensett, a prominent 19th-century American landscape painter associated with the Hudson River School.
-
C.
Abbott
Abbott is a masculine given name of English origin, historically associated with clerical or religious roles.
-
D.
Abbott
Abbott is a common English surname borne by numerous notable individuals across fields such as politics, entertainment, science, and business.
-
E.
Swanson
Swanson is a well-known American food brand recognized for its canned broths, stocks, and frozen meals.
- 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_69c68827b5e481908dc05e145b2c92d4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea58533481909af7a4a6ade40eff |
completed | March 27, 2026, 8:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7d3987a888190ab19915b39dbf7eb |
completed | March 28, 2026, 1:11 p.m. |
Created at: March 27, 2026, 2:56 p.m.