Triple
T11181699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adorn (Remix) |
E264554
|
entity |
| Predicate | isRemixOf |
P9639
|
FINISHED |
| Object | Adorn |
E49774
|
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: Adorn | Statement: [Adorn (Remix), isRemixOf, Adorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adorn Context triple: [Adorn (Remix), isRemixOf, Adorn]
-
A.
Adorn
chosen
"Adorn" is a Grammy-winning R&B single by American singer Miguel, known for its smooth vocals and sensual, minimalist production.
-
B.
Splendore
Splendore is a novel by Italian author Margaret Mazzantini that explores themes of identity, love, and self-discovery.
-
C.
The Ornaments of Gold
The Ornaments of Gold is the English rendering of the Arabic title "Az-Zukhruf," referring to the 43rd chapter of the Qur’an, which discusses themes of worldly adornment versus true spiritual value.
-
D.
Tailo
Tailo is a widely used Latin-based romanization system for writing Taiwanese Hokkien, employed in education, literature, and language preservation.
-
E.
Ourique
Ourique is a rural municipality in Portugal’s Alentejo region, known for its historical links to the legendary Battle of Ourique and its traditional agricultural landscape.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8a7f35481909f35feb94ef10e80 |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4acf79b748190b117355f60c8c015 |
completed | April 19, 2026, 10:22 a.m. |
Created at: April 8, 2026, 9:29 p.m.