Triple
T21075072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seville bus network |
E519210
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | city of Seville |
—
|
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: city of Seville | Statement: [Seville bus network, serves, city of Seville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: city of Seville Context triple: [Seville bus network, serves, city of Seville]
-
A.
Seville, Spain
chosen
Seville, Spain is a historic Andalusian city renowned for its Moorish-influenced architecture, vibrant flamenco culture, and landmarks such as the Seville Cathedral and the Alcázar.
-
B.
Seville
Seville is a historic Spanish city in Andalusia renowned for its rich Moorish and Christian heritage, iconic landmarks like the Giralda and Alcázar, and vibrant cultural traditions such as flamenco.
-
C.
Seville
Seville is a small unincorporated rural community located in Volusia County, Florida, known for its agricultural surroundings and historic character.
-
D.
Sevilla
Sevilla is a station on Madrid's Metro network, serving Line 2 in the city center.
-
E.
Sevilla
Sevilla is a Mexico City Metro station on Line 1, located in the central area of the city and serving nearby commercial and residential zones.
- 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_69e0b506e59c8190849b71ed07929215 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e702d5ae908190ab5303e39443d729 |
completed | April 21, 2026, 4:53 a.m. |
Created at: April 16, 2026, 2:48 p.m.