Triple
T8972199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian Boru harp |
E214292
|
entity |
| Predicate | inspired |
P9
|
FINISHED |
| Object | Guinness logo harp |
E250800
|
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: Guinness logo harp | Statement: [Brian Boru harp, inspired, Guinness logo harp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guinness logo harp Context triple: [Brian Boru harp, inspired, Guinness logo harp]
-
A.
Guinness
chosen
Guinness is a world-famous Irish dry stout brand originating from Dublin and known for its dark color, creamy head, and long brewing heritage.
-
B.
Arthur Guinness & Son
Arthur Guinness & Son was the family-run brewing company behind Guinness stout, one of Ireland’s most famous and globally recognized beer brands.
-
C.
Hugo Guinness
Hugo Guinness is a British artist, illustrator, and writer known for his linocut prints and collaborations with filmmaker Wes Anderson.
-
D.
Red Swoosh
Red Swoosh was a peer-to-peer content delivery and file-sharing startup later acquired by Akamai Technologies.
-
E.
Guinness Trust
The Guinness Trust is a British charitable housing association established in the late 19th century to provide affordable homes and improve living conditions for the urban poor.
- 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_69ca839dbf608190a2f5990477115d29 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6780d45081909f2bc5295c8550f9 |
completed | April 1, 2026, 12:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc9632afc8190a4dc14d33e8757ee |
completed | April 3, 2026, 2:06 p.m. |
Created at: March 30, 2026, 7:02 p.m.