Triple
T18109475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frou Frou |
E433433
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Björk |
—
|
NE NERFINISHED |
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: Björk | Statement: [Frou Frou, associatedAct, Björk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Björk Context triple: [Frou Frou, associatedAct, Björk]
-
A.
Bjork
chosen
Björk is an Icelandic singer, songwriter, and producer known for her innovative, genre-blending music, distinctive voice, and avant-garde visual style.
-
B.
Lykke Li
Lykke Li is a Swedish indie pop singer-songwriter known for her atmospheric, melancholic sound and hits like "I Follow Rivers."
-
C.
Dóra
Dóra is a Hungarian given name most notably borne by the conceptual and experimental artist Dóra Maurer.
-
D.
Joanna Newsom
Joanna Newsom is an American singer-songwriter and harpist known for her intricate compositions, poetic lyrics, and distinctive vocal style.
-
E.
Enya
Enya is an Irish singer, songwriter, and musician renowned for her ethereal, multi-layered vocal style and atmospheric new-age music that has achieved worldwide commercial success.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd13cb48190bff06b472e34dd0e |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:28 a.m.