Triple
T3662478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henrietta |
E77681
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Henriette |
E211775
|
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: Henriette | Statement: [Henrietta, hasVariant, Henriette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henriette Context triple: [Henrietta, hasVariant, Henriette]
-
A.
Henriette
chosen
Henriette is the given first name of the French photographer and painter Dora Maar, renowned for her association with Pablo Picasso and the Surrealist movement.
-
B.
Henrietta
Henrietta is a suburban community in western New York State, located near Rochester within the Rust Belt region along the Interstate 90 corridor.
-
C.
Henrietta
Henrietta is a feminine given name of English origin, historically popular in the 18th and 19th centuries and borne by several notable figures.
-
D.
Mariette
Mariette is a French feminine given name, commonly used as a diminutive or affectionate form of Marie.
-
E.
Marie
Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3fcd910819082012b10b23860aa |
completed | March 8, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48846af9881909d71d63b8bd8d141 |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.