Triple
T954332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clement |
E20592
|
entity |
| Predicate | hasFeminineForm |
P1613
|
FINISHED |
| Object | Clémentine |
E27357
|
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: Clémentine | Statement: [Clement, hasFeminineForm, Clémentine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clémentine Context triple: [Clement, hasFeminineForm, Clémentine]
-
A.
Clémentine
chosen
Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
-
B.
Micheline
Micheline is a feminine given name of French origin, commonly used in French-speaking countries.
-
C.
Estelle
Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
-
D.
Pierrette
Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
-
E.
Carine
Carine is a feminine given name, often considered a variant of names like Catherine or Karine, used in various European languages.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3da8d508190b56b29d7f235d2c4 |
completed | March 1, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4287830c819095ffc30fc03a7461 |
completed | March 7, 2026, 3:21 p.m. |
Created at: March 1, 2026, 7:40 p.m.