Triple
T15339102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zoolander 2 |
E366742
|
entity |
| Predicate | setIn |
P1393
|
FINISHED |
| Object | Italy |
E863
|
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: Italy | Statement: [Zoolander 2, setIn, Italy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Italy Context triple: [Zoolander 2, setIn, Italy]
-
A.
Italy
Italy is a small rural town in Yates County, New York, known for its agricultural landscape and location in the Finger Lakes region.
-
B.
Italy
chosen
Italy is a Southern European country known for its influential history, art, cuisine, and role as a founding member of the European Union.
-
C.
Italia
Italia is a feminine given name, often inspired by the country of Italy and used in various cultures.
-
D.
Włochy
Włochy is a district in the southwestern part of Warsaw, Poland, known for its mix of residential areas, industrial zones, and major transport infrastructure including the city’s main airport.
-
E.
Como, Italy
Como, Italy is a picturesque city in northern Italy’s Lombardy region, renowned for its historic architecture and its location at the southern tip of Lake Como.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e12eb7c8190944a260aa1aa9156 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01e9d14c8190bb095d6d5c8ffd6e |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:17 a.m.