Triple
T13729922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishop of Avellaneda |
E329769
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Avellaneda |
E329768
|
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: Avellaneda | Statement: [Bishop of Avellaneda, locatedIn, Avellaneda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avellaneda Context triple: [Bishop of Avellaneda, locatedIn, Avellaneda]
-
A.
Avellaneda
chosen
Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
-
B.
Ossorio
Ossorio is a Spanish-origin surname notably borne by Filipino-American abstract expressionist artist Alfonso Ossorio.
-
C.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
D.
Almagro
Almagro is a traditional middle-class neighborhood in central Buenos Aires, Argentina, known for its historic tango culture, cafes, and densely populated residential streets.
-
E.
Almagro
Almagro is a Spanish surname borne by various notable figures, including politicians, athletes, and artists from Spanish-speaking countries.
- 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_69d80772315881908f980cae40d91664 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de01f746cc8190abde237bbb7e6c78 |
completed | April 14, 2026, 8:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d65062c819086a5f7a7ebc45412 |
completed | May 3, 2026, 7:09 p.m. |
Created at: April 9, 2026, 9:55 p.m.