Triple
T11975976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cauca |
E285040
|
entity |
| Predicate | locatedInPresentDay |
P40
|
FINISHED |
| Object | Coca |
E385557
|
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: Coca | Statement: [Cauca, locatedInPresentDay, Coca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coca Context triple: [Cauca, locatedInPresentDay, Coca]
-
A.
Coca
chosen
Coca is a small city in Ecuador that serves as a key gateway to the Amazon rainforest and regional oil operations.
-
B.
Cocaine
Cocaine is a powerful and addictive stimulant drug derived from the coca plant, known for its euphoric effects and significant health and legal risks.
-
C.
Rum and Coca-Cola
"Rum and Coca-Cola" is a popular 1944 calypso-style song, famously recorded by the Andrews Sisters, that became a major World War II–era hit.
-
D.
Ganja
Ganja is one of Azerbaijan’s largest and oldest cities, known as a historic cultural and economic center in the South Caucasus.
-
E.
Sabu
Sabu is a pioneering hardcore professional wrestler best known for his extreme, high-risk style and influential run in ECW.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903926690819090e7ce982f103457 |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f471e608e881908d45558d6251af9e |
completed | May 1, 2026, 9:27 a.m. |
Created at: April 8, 2026, 9:46 p.m.