Triple
T22640665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenida de Aragón |
E558814
|
entity |
| Predicate | connectsToDirection |
P40705
|
FINISHED |
| Object | Zaragoza |
—
|
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: Zaragoza | Statement: [Avenida de Aragón, connectsToDirection, Zaragoza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zaragoza Context triple: [Avenida de Aragón, connectsToDirection, Zaragoza]
-
A.
Zaragoza
Zaragoza is a historic city in northeastern Spain, known for landmarks like the Basilica del Pilar and its role as a major cultural and economic center in the Aragon region.
-
B.
Zaragoza
chosen
Zaragoza is a metro station on Mexico City’s Line 1 that serves as a key eastern access point to the city’s rapid transit network.
-
C.
Zaragoza
Zaragoza is a small municipality and town in the northern Mexican state of Coahuila, known for its rural character and proximity to the U.S. border.
-
D.
Zaragoza
Zaragoza is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
-
E.
Zaragoza
Zaragoza is a municipality in the La Libertad Department of El Salvador, known for its growing suburban communities near the capital, San Salvador.
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f170116fe881908178cffef26e3ae7 |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:04 p.m.