Triple
T4943867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dido |
E110999
|
entity |
| Predicate | nameVariant |
P744
|
FINISHED |
| Object | Alyssa |
E439124
|
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: Alyssa | Statement: [Dido, nameVariant, Alyssa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alyssa Context triple: [Dido, nameVariant, Alyssa]
-
A.
Alyssa
chosen
Alyssa is a feminine given name that gained widespread popularity in the late 20th century, partly due to its use by American actress Alyssa Milano.
-
B.
Ashley
Ashley is a small village and civil parish located within the county of Suffolk in eastern England.
-
C.
Ashley
Ashley is a character featured in the animated children’s series "¡Dos!"
-
D.
Ashley
Ashley is a given name commonly used in English-speaking countries for both males and females.
-
E.
Alana
Alana is a feminine given name commonly used in English-speaking countries and various cultures worldwide.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70a7650c8190b046b65072fd8eae |
completed | March 20, 2026, 4:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be77c6566c8190b0c76c05b9d82053 |
completed | March 21, 2026, 10:49 a.m. |
Created at: March 20, 2026, 1:31 p.m.