Triple
T2839563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walgreens Boots Alliance |
E62430
|
entity |
| Predicate | hasMajorBrand |
P40804
|
FINISHED |
| Object | Boots |
E302747
|
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: Boots | Statement: [Walgreens Boots Alliance, hasMajorBrand, Boots]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boots Context triple: [Walgreens Boots Alliance, hasMajorBrand, Boots]
-
A.
Boots
Boots is an American singer, songwriter, and record producer best known for his influential work on Beyoncé’s self-titled 2013 album.
-
B.
Boots
chosen
Boots is a major British pharmacy-led health and beauty retailer and pharmacy chain with stores across the United Kingdom and other countries.
-
C.
Bata
Bata is a major port city on the mainland of Equatorial Guinea, serving as a key economic and transportation hub for the country.
-
D.
Coogs
Coogs is a common shorthand nickname for the University of Houston Cougars athletic teams and their fans.
-
E.
Scarpe
The Scarpe is a river in northern France that flows through the Artois and Nord regions before joining the Scheldt.
- 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_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe08ae5048190a0a3b573d9a5fdbc |
completed | March 7, 2026, 8:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01d7705108190a986d3def0c08f7b |
completed | March 10, 2026, 1:32 p.m. |
Created at: March 6, 2026, 10:01 p.m.