Triple
T14179606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Three Tales |
E351417
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | Charpentier |
E225104
|
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: Charpentier | Statement: [Three Tales, publisher, Charpentier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charpentier Context triple: [Three Tales, publisher, Charpentier]
-
A.
Charpentier
chosen
Charpentier is a French surname borne by various notable individuals across fields such as science, arts, and politics.
-
B.
Gauthier
Gauthier is a French given name and surname, equivalent to the English name Walter and historically borne by various notable figures in France and other Francophone regions.
-
C.
Roussel
Roussel is a surname of French origin, often used as an alternative spelling of Russell.
-
D.
Oudry
Oudry is the surname of Jean-Baptiste Oudry, an 18th-century French painter and engraver renowned for his animal and hunting scenes.
-
E.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61c90abc8190a9b9dc1f50db59fa |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd280656a881909c565b99e85ae9bd |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:02 a.m.