Triple
T18816847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maranello |
E460157
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Güines |
—
|
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: Güines | Statement: [Maranello, twinTown, Güines]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Güines Context triple: [Maranello, twinTown, Güines]
-
A.
Güines
chosen
Güines is a town and municipality in western Cuba known historically as an important agricultural and sugar-producing center southeast of Havana.
-
B.
Grenada
Grenada is a small Caribbean island nation known for its spice production, picturesque beaches, and lush mountainous interior.
-
C.
San Cristóbal
San Cristóbal is a locality situated within Colombia’s Bolívar Department, known as part of the Caribbean region of the country.
-
D.
San Cristóbal
San Cristóbal is the former name of the historic highland city now known as San Cristóbal de las Casas in the Mexican state of Chiapas.
-
E.
San Cristóbal
San Cristóbal is a major Andean city in western Venezuela and the capital of Táchira state, known as a regional commercial and cultural center near the Colombian border.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a6b620248190afa21a6ce61e2cff |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 10, 2026, 11:55 a.m.