Triple
T15546723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylacauga, Alabama |
E370627
|
entity |
| Predicate | hasNickName |
P39
|
FINISHED |
| Object | Marble City |
E604727
|
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: Marble City | Statement: [Sylacauga, Alabama, hasNickName, Marble City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marble City Context triple: [Sylacauga, Alabama, hasNickName, Marble City]
-
A.
Marble City
chosen
Marble City is a nickname for Sylacauga, Alabama, reflecting its long history of marble quarrying and production.
-
B.
Marble City
Marble City is the nickname of Kilkenny, an Irish city famed for its distinctive black limestone and historic architecture.
-
C.
Ochre City
Ochre City is a popular nickname for Marrakesh, referring to the Moroccan city's distinctive red and ochre-colored buildings and walls.
-
D.
Mima City
Mima City is a municipality in western Tokushima Prefecture, Japan, known for its historic townscapes, traditional indigo dyeing culture, and scenic rural landscapes.
-
E.
Limestone City
Limestone City is a nickname for Kingston, Ontario, reflecting its many historic buildings constructed from local limestone.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a9073948190b6e9cf504aacc7cf |
completed | April 16, 2026, 2:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff455c172c8190833274cb98667e84 |
completed | May 9, 2026, 2:31 p.m. |
Created at: April 10, 2026, 4:08 a.m.