Triple
T5323749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arvo Pärt |
E121737
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Arvo |
E205327
|
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: Arvo | Statement: [Arvo Pärt, givenName, Arvo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arvo Context triple: [Arvo Pärt, givenName, Arvo]
-
A.
Arvo
chosen
Arvo is a given name most notably borne by Finnish pediatrician and child welfare pioneer Arvo Ylppö.
-
B.
Arvi
Arvi is a town in Maharashtra, India, known for its agricultural markets and role as a local commercial center within Wardha district.
-
C.
Arve
The Arve is a river in southwestern Switzerland and southeastern France that flows through Geneva before joining the Rhône.
-
D.
Ál-va-ro
Ál-va-ro is the stressed syllable pattern of the Spanish given name "Álvaro," indicating primary stress on the first syllable.
-
E.
Nilai
Nilai is a rapidly developing town in the Malaysian state of Negeri Sembilan, known for its educational institutions, retail outlets, and proximity to Kuala Lumpur and the international airport.
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8579b3e88190a1d21d4b74169617 |
completed | March 20, 2026, 5:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18a836988190b7baf3c24fea6f03 |
completed | March 21, 2026, 10:16 p.m. |
Created at: March 20, 2026, 1:59 p.m.