Triple
T16745524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan French |
E406940
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | French of France |
E13984
|
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: French of France | Statement: [Metropolitan French, hasAlternativeName, French of France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: French of France Context triple: [Metropolitan French, hasAlternativeName, French of France]
-
A.
Franzese
Franzese is an Italian surname borne by various notable individuals in fields such as entertainment and organized crime.
-
B.
Louis (French)
Louis is the French given name corresponding to the name Ludwik in other languages.
-
C.
The French
The French is a renowned fine-dining restaurant in Manchester’s Midland Hotel, known for its modern British cuisine and historic, elegant setting.
-
D.
French American
French Americans are U.S. residents or citizens of French ancestry, including both descendants of early French settlers and more recent immigrants from France.
-
E.
French
chosen
French is a Romance language that evolved from Latin and is now spoken worldwide as both a native and official language in many countries.
- 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_69e3aa223aa88190a3c1805ece7317e2 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a52033748190ae207d72d437236b |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.