Triple
T12205076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abiquiu |
E290814
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Espanola |
E290811
|
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: Espanola | Statement: [Abiquiu, nearbyCity, Espanola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Espanola Context triple: [Abiquiu, nearbyCity, Espanola]
-
A.
Espanola
chosen
Española is a small city in northern New Mexico known for its location in the Rio Grande Valley and its blend of Hispanic and Native American cultural heritage.
-
B.
Espanola
Espanola is a small town in Northern Ontario, Canada, known historically for its pulp and paper industry and its location near the North Channel of Lake Huron.
-
C.
Tasqueña
Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
-
D.
Tagüeña
Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
-
E.
Guipago
Guipago, also known as Lone Wolf, was a prominent 19th-century Kiowa chief and warrior who led his people in resistance against U.S. expansion onto their lands.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c7c9084819085e7d2f9038f409f |
completed | April 10, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a9ae3d48190a220ccd37ce8d3e7 |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:51 p.m.