Triple
T2906904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francisco |
E62786
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object | François (French) |
E284329
|
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: François (French) | Statement: [Francisco, hasCognate, François (French)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: François (French) Context triple: [Francisco, hasCognate, François (French)]
-
A.
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.
-
B.
French
French is a Romance language that evolved from Latin and is now spoken worldwide as both a native and official language in many countries.
-
C.
Fran
Fran is a common shortened given name, typically used as a diminutive of Frances or Francis.
-
D.
Alain (French)
chosen
Alain is the French given name equivalent to the English name Alan, commonly used for males in French-speaking countries.
-
E.
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.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe0d0628c81909680af2f0db2ecae |
completed | March 7, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b05612e79081908c962c2fe2e362d6 |
completed | March 10, 2026, 5:34 p.m. |
Created at: March 6, 2026, 10:11 p.m.