Triple
T9147056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mandy |
E219482
|
entity |
| Predicate | hasVariantForm |
P457
|
FINISHED |
| Object | Mandy (as nickname) |
E251419
|
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: Mandy (as nickname) | Statement: [Mandy, hasVariantForm, Mandy (as nickname)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mandy (as nickname) Context triple: [Mandy, hasVariantForm, Mandy (as nickname)]
-
A.
Maddy
Maddy is a common diminutive or nickname typically used for the given name Madison.
-
B.
Marilynne
Marilynne is the given name of Marilynne Robinson, the acclaimed American novelist and essayist known for works such as "Housekeeping" and the "Gilead" series.
-
C.
Mia
Mia is a major fine art museum in Minneapolis, Minnesota, known for its extensive and diverse collection spanning thousands of years and cultures.
-
D.
Mia
Mia is a feminine given name used in many cultures, often as a short form of names like Maria or Amelia.
-
E.
Madelyn
chosen
Madelyn is a feminine given name, often considered a modern variant of Madeline and commonly used in English-speaking countries.
- 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_69ca83e121dc81909912bd66953081c5 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca918a3c881909c34a6a682eb2625 |
completed | April 1, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0482995cc81909bfc202cbab7f8a1 |
completed | April 3, 2026, 11:07 p.m. |
Created at: March 30, 2026, 7:20 p.m.