Triple
T10089442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maurice Renard |
E215304
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Maurice |
E44841
|
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: Maurice | Statement: [Maurice Renard, givenName, Maurice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maurice Context triple: [Maurice Renard, givenName, Maurice]
-
A.
Maurice
chosen
Maurice is a masculine given name of Latin origin, commonly used in English and French-speaking countries.
-
B.
Maurice
Maurice is a 1987 British romantic drama film, based on E.M. Forster’s novel, that explores same-sex love and class in early 20th-century England.
-
C.
Marcel
Marcel is a masculine given name of French origin, commonly used in various European countries.
-
D.
Marcel
Marcel is an American country music singer-songwriter who recorded for the Nashville-based label Lyric Street Records.
-
E.
Swann
Swann is a surname most prominently associated with Lynn Swann, a Hall of Fame American football wide receiver and former politician.
- 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd057e32881908bf630559af94906 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b69cd26c8190bf4b488377dc0ce1 |
completed | April 5, 2026, 7:23 p.m. |
Created at: March 30, 2026, 9:01 p.m.