Triple
T9348232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Colombia |
E224947
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Florencia |
E703998
|
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: Florencia | Statement: [Southern Colombia, hasCity, Florencia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Florencia Context triple: [Southern Colombia, hasCity, Florencia]
-
A.
Florencia
Florencia is a street in Mexico City that intersects at the Glorieta del Ángel, a major roundabout surrounding the iconic Angel of Independence monument.
-
B.
Florencia
chosen
Florencia is a city in southern Colombia that serves as a key gateway between the Andean region and the Amazon rainforest.
-
C.
San Juan de Flores
San Juan de Flores is a municipality in central Honduras known for its rural character and location within the Francisco Morazán Department.
-
D.
Concepción
Concepción was one of the ships in Ferdinand Magellan’s expedition that took part in the first circumnavigation of the globe.
-
E.
Concepción
Concepción is a city in northern Paraguay known as a regional commercial and river port hub.
- 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_69ca842993248190a79ab06968994b86 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f107f0081908938f4b814eca5fc |
completed | April 1, 2026, 5 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1220b4be48190aecba672fd10d035 |
completed | April 4, 2026, 2:36 p.m. |
Created at: March 30, 2026, 7:41 p.m.