Triple
T15029081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Artur Paredes |
E378293
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Artur |
E325012
|
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: Artur | Statement: [Artur Paredes, givenName, Artur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Artur Context triple: [Artur Paredes, givenName, Artur]
-
A.
Artur
chosen
Artur is a masculine given name of Celtic origin, commonly used in various European countries and often associated with the legendary King Arthur.
-
B.
Guiderius
Guiderius is a noble prince and one of the central heroic figures in William Shakespeare’s play "Cymbeline," known for his bravery and hidden royal identity.
-
C.
Gustaw
Gustaw is a masculine given name of Slavic origin, particularly common in Poland.
-
D.
Ingenried
Ingenried is a small rural municipality in the Weilheim-Schongau district of Bavaria in southern Germany.
-
E.
Raszar
Raszar is a cinematographer known for his work on the film "Human Traffic."
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e0e8c88190ac6f5786b4d4040f |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dd967588190821cf47e9734db21 |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 2:58 a.m.