Triple
T14431269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melinda Katz |
E357832
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Melinda |
E1000618
|
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: Melinda | Statement: [Melinda Katz, givenName, Melinda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melinda Context triple: [Melinda Katz, givenName, Melinda]
-
A.
Melinda
Melinda is the first name of Melinda French Gates, an American philanthropist and co-founder of the Bill & Melinda Gates Foundation.
-
B.
Melinda
Melinda is a young, impressionable girl in the play "Inherit the Wind," serving as a minor character who reflects the town’s attitudes during the famous trial.
-
C.
Melinda
Melinda is a central female character in George Farquhar’s Restoration comedy "The Recruiting Officer," known for her wit, independence, and role in the play’s romantic intrigues.
-
D.
Melinda
chosen
Melinda is a feminine given name of Greek origin, commonly used in English-speaking countries.
-
E.
Melinda
"Melinda" is a musical number from the stage and film musical *On a Clear Day You Can See Forever*, known for its romantic, melodic style.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de914570f08190b1c7c1c57a0cb476 |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd648b8f348190be11645b371b4102 |
completed | May 8, 2026, 4:20 a.m. |
Created at: April 10, 2026, 1:18 a.m.