Triple
T16263581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cairo, Georgia |
E394814
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Syrup City |
E650577
|
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: Syrup City | Statement: [Cairo, Georgia, nickname, Syrup City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Syrup City Context triple: [Cairo, Georgia, nickname, Syrup City]
-
A.
Syrup City
chosen
Syrup City is the nickname of Cairo, a small city in southern Georgia known historically for its syrup production and related agricultural industry.
-
B.
Sugar City
Sugar City is the popular nickname for Lautoka, a major Fijian city renowned for its prominent sugar industry and large sugar mill.
-
C.
Sugar City
Sugar City is the nickname of Victorias, a city in the Philippines renowned for its large sugar industry and sugarcane plantations.
-
D.
Soda City
Soda City is a popular nickname for Columbia, South Carolina, reflecting the city's historic association with the soft drink industry and its vibrant local culture.
-
E.
Parlor City
Parlor City is a historic nickname for Binghamton, New York, reflecting its past reputation as a refined, prosperous urban center.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c672248190a4261be4696d52c5 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0017b5f3a8819083128cf2b90cfd84 |
completed | May 10, 2026, 5:29 a.m. |
Created at: April 10, 2026, 5:04 a.m.