Triple
T7930787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AbbVie |
E184183
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Abbott Laboratories |
E49343
|
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: Abbott Laboratories | Statement: [AbbVie, foundedBy, Abbott Laboratories]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abbott Laboratories Context triple: [AbbVie, foundedBy, Abbott Laboratories]
-
A.
Abbott Laboratories
chosen
Abbott Laboratories is a global healthcare company that develops and manufactures medical devices, diagnostics, branded generic medicines, and nutritional products.
-
B.
Pharmaceutical Research and Manufacturers of America
Pharmaceutical Research and Manufacturers of America is a major U.S. trade association representing leading biopharmaceutical and drug research companies.
-
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.
Johnson & Johnson
Johnson & Johnson is a multinational healthcare conglomerate best known for its pharmaceuticals, medical devices, and consumer health products.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3accc388819087065ebe7d5d9591 |
completed | March 31, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5c01602081908ea1af24785260ff |
completed | March 31, 2026, 5:30 a.m. |
Created at: March 30, 2026, 5:07 p.m.