Triple
T19603484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trnava |
E470542
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Little Rome |
—
|
NE NERFINISHED |
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: Little Rome | Statement: [Trnava, nickname, Little Rome]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Little Rome Context triple: [Trnava, nickname, Little Rome]
-
A.
Little Rome
Little Rome is a nickname for the Sri Lankan city of Negombo, known for its numerous Catholic churches and strong Christian heritage.
-
B.
Little Rome
chosen
Little Rome is a nickname for the Slovak city of Trnava, known for its numerous historic churches and strong Catholic heritage.
-
C.
Romee
Romee is a Dutch fashion model best known for her work as a Victoria’s Secret Angel.
-
D.
Palermo Chico
Palermo Chico is an affluent, embassy-filled residential enclave in Buenos Aires known for its elegant architecture and proximity to major parks and museums.
-
E.
Roma Sur
Roma Sur is a vibrant neighborhood in Mexico City known for its mix of historic architecture, cultural venues, and trendy restaurants and cafes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64081af6c8190868b73b07c874cd5 |
completed | April 20, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:43 p.m.