Triple
T17648270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Perla |
E429417
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Atzacan |
—
|
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: Atzacan | Statement: [La Perla, borderedBy, Atzacan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Atzacan Context triple: [La Perla, borderedBy, Atzacan]
-
A.
Atzacan
chosen
Atzacan is a municipality in the Mexican state of Veracruz that forms part of the greater Orizaba metropolitan region.
-
B.
Tototlán
Tototlán is a municipality and town in the Mexican state of Jalisco, known for its agricultural economy and traditional regional culture.
-
C.
Zacatlán
Zacatlán is a historic town in the Mexican state of Puebla, renowned for its apple production, cider, and scenic mountain landscapes.
-
D.
Tejutla
Tejutla is a municipality located in the highland region of western Guatemala, known for its rural communities and traditional agricultural activities.
-
E.
Cuautlancingo
Cuautlancingo is a municipality and rapidly growing suburban city in the Mexican state of Puebla, integrated into the greater Puebla metropolitan area.
- 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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46e3a5ad8819085d4bef669fc3152 |
completed | April 19, 2026, 5:55 a.m. |
Created at: April 10, 2026, 6:05 a.m.