Triple
T14663810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matilda |
E344311
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Mathilda |
E870807
|
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: Mathilda | Statement: [Matilda, hasVariant, Mathilda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mathilda Context triple: [Matilda, hasVariant, Mathilda]
-
A.
Mathilda
chosen
Mathilda is the young girl in the film "Léon: The Professional" who becomes the protégé of a solitary hitman after her family is murdered.
-
B.
Mathilda
Mathilda is the middle name of Elivera Mathilda Carlson Doud, the wife of former U.S. President Dwight D. Eisenhower.
-
C.
Matilde
Matilde is a feminine given name of Spanish and Portuguese origin, related to the name Matilda and historically borne by various notable women.
-
D.
Lucile
Lucile is a popular 1860 verse novel by British writer Edward Bulwer-Lytton, known for its romantic plot and melodramatic style.
-
E.
Lucile
Lucile is a feminine given name of Latin origin, commonly associated with the name Lucille and meaning "light."
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54ae5ac81908cc69891f280e5f7 |
completed | April 14, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5e4789481909a64622a1d284373 |
completed | May 8, 2026, 12:24 p.m. |
Created at: April 10, 2026, 1:27 a.m.