Triple
T2266533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palermo (Buenos Aires) |
E50157
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Palermo Chico |
E50157
|
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: Palermo Chico | Statement: [Palermo (Buenos Aires), hasPart, Palermo Chico]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palermo Chico Context triple: [Palermo (Buenos Aires), hasPart, Palermo Chico]
-
A.
Logudoro
Logudoro is a historical-cultural region in northern Sardinia known for its distinctive Sardinian dialect, medieval heritage, and rural landscapes.
-
B.
Porto Ercole
Porto Ercole is a coastal village on Italy’s Monte Argentario peninsula, known as a historic Tuscan port and the place where the painter Caravaggio died.
-
C.
Cagli
Cagli is a historic town in Italy’s Marche region, known for its medieval architecture and scenic setting in the Apennine foothills.
-
D.
Locana
Locana is a seminal Sanskrit commentary by the Kashmiri philosopher Abhinavagupta, best known for its influential exposition of Indian aesthetic theory and poetics.
-
E.
Palermo
chosen
Palermo is a large, upscale neighborhood in Buenos Aires known for its parks, nightlife, cultural attractions, and trendy dining and shopping areas.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc18fff0c8190acd73d8db8a41cff |
completed | March 7, 2026, 6:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71d492a48190be58396831e87ea0 |
completed | March 9, 2026, 7:08 a.m. |
Created at: March 4, 2026, 7:48 p.m.