Triple
T4659120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiat 124 |
E102483
|
entity |
| Predicate | assembly |
P19323
|
FINISHED |
| Object | Turin, Italy |
E15144
|
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: Turin, Italy | Statement: [Fiat 124, assembly, Turin, Italy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turin, Italy Context triple: [Fiat 124, assembly, Turin, Italy]
-
A.
Turin
chosen
Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and economic hub.
-
B.
Turin
Turin is a small town located in Coweta County in the U.S. state of Georgia.
-
C.
Metropolitan City of Turin
The Metropolitan City of Turin is an Italian administrative region in Piedmont that encompasses the city of Turin and its surrounding municipalities, coordinating local governance, infrastructure, and regional development.
-
D.
Tivoli, Italy
Tivoli, Italy is a historic town near Rome renowned for its ancient villas, spectacular gardens, and scenic waterfalls.
-
E.
Milan
Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
- 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_69bd43d823288190952279faa0d1d066 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd63271a548190bd9662b69a45d9a5 |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4d739e9c8190b7fffe68a3b54de5 |
completed | March 21, 2026, 7:49 a.m. |
Created at: March 20, 2026, 1:15 p.m.