Triple
T16744362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Margaretha of Luxembourg |
E406911
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Margaretha |
E113357
|
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: Margaretha | Statement: [Princess Margaretha of Luxembourg, givenName, Margaretha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margaretha Context triple: [Princess Margaretha of Luxembourg, givenName, Margaretha]
-
A.
Margareta
chosen
Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
-
B.
Brigitta
Brigitta is a character based on one of the real-life von Trapp children, featured as one of the daughters in "The Sound of Music."
-
C.
Hjördis
Hjördis is a Scandinavian feminine given name, most notably borne by Swedish model and actress Hjördis Genberg.
-
D.
Maddalene
Maddalene is a feminine given name, typically considered a variant of Maddalena or Magdalene, with roots in Christian and European naming traditions.
-
E.
Birgitte
Birgitte is a Danish-born member of the British royal family who holds the title Duchess of Gloucester.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa210ef88190be74bd60d7144953 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a51e69c08190a5bff74823df430c |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.