Triple
T21197319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marian Langiewicz |
E522359
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marian |
—
|
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: Marian | Statement: [Marian Langiewicz, givenName, Marian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marian Context triple: [Marian Langiewicz, givenName, Marian]
-
A.
Marian
chosen
Marian is a given name of Latin origin commonly used in various European countries for both males and females.
-
B.
Marian
Marian is a small rural town and sugar-growing community in Queensland, Australia, located within the Mackay Region.
-
C.
Marjory
Marjory is a feminine given name, commonly considered a variant spelling of Marjorie.
-
D.
Mary Dole
Mary Dole is a person notable enough to be recognized as a bearer of the surname Dole, though specific widely known biographical details about her are not clearly established.
-
E.
Mariann
Mariann is the given name of Mariann Edgar Budde, an American Episcopal bishop known for her leadership in the Episcopal Diocese of Washington.
- 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7333c9bac8190a203802a8b8e4143 |
completed | April 21, 2026, 8:20 a.m. |
Created at: April 16, 2026, 3:11 p.m.