Triple
T13559603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Océan-class ship of the line |
E323869
|
entity |
| Predicate | designedBy |
P184
|
FINISHED |
| Object | Jacques-Noël Sané |
E335571
|
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: Jacques-Noël Sané | Statement: [Océan-class ship of the line, designedBy, Jacques-Noël Sané]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jacques-Noël Sané Context triple: [Océan-class ship of the line, designedBy, Jacques-Noël Sané]
-
A.
Jacques-Noël Sané
chosen
Jacques-Noël Sané was a prominent 18th–19th century French naval engineer renowned for designing many of the French Navy’s most successful ships of the line.
-
B.
Luc Teyssier
Luc Teyssier is a charming, roguish French thief who becomes the romantic lead opposite Meg Ryan’s character in the 1995 romantic comedy film "French Kiss."
-
C.
Pierre Chambiges
Pierre Chambiges was a prominent 16th-century French Renaissance architect best known for his influential work on major Parisian civic and religious buildings.
-
D.
François Lecointre
François Lecointre is a French Army general who served as France’s Chief of the Defence Staff.
-
E.
Jean-François Joanny
Jean-François Joanny is a French physicist known for his influential work in soft condensed matter and polymer physics.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaff4223c8190801d153ae8f94c73 |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75dab4974819097880ad4d50f1b34 |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:47 p.m.