Triple
T13539306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sissy Rommely |
E323340
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Rommely |
E1045128
|
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: Rommely | Statement: [Sissy Rommely, familyName, Rommely]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rommely Context triple: [Sissy Rommely, familyName, Rommely]
-
A.
Rommely
chosen
Rommely is the surname of the fictional Rommely family featured in Betty Smith’s novel "A Tree Grows in Brooklyn."
-
B.
Romm
Romm is a surname most notably associated with Soviet film director and screenwriter Mikhail Romm.
-
C.
Romilda
Romilda is a principal female character in Handel’s opera "Serse," known for being the object of the title character’s romantic pursuit and for her own love for another man.
-
D.
Ramel
Ramel is a Swedish surname most notably associated with the entertainer and composer Povel Ramel.
-
E.
Romita
Romita is a town in the Mexican state of Guanajuato that serves as the administrative and population center of the surrounding Romita Municipality.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafd7ad9481908fe1d7ffcf8fab71 |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76babfb948190bc028450ddaa0b72 |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:45 p.m.