Triple
T13307702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Gorizia |
E316978
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
GO
GO is the vehicle registration code used on license plates for vehicles registered in the Province of Gorizia in northeastern Italy.
|
E1032119
|
NE FINISHED |
How this triple was built (4 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: GO | Statement: [Province of Gorizia, vehicleRegistrationCode, GO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GO Context triple: [Province of Gorizia, vehicleRegistrationCode, GO]
-
A.
Go
Go is an ancient East Asian abstract strategy board game, renowned for its simple rules yet immense strategic depth, played on a grid with black and white stones.
-
B.
Go
Go is a 1961 hard bop jazz album by bassist Paul Chambers, showcasing his work as a bandleader with a small ensemble.
-
C.
Go
Go is a statically typed, compiled programming language developed at Google, known for its simplicity, efficient concurrency support, and suitability for scalable networked and cloud services.
-
D.
Go
"Go" is a surf rock song, likely characterized by upbeat rhythms and guitar-driven melodies typical of the genre.
-
E.
Go
Go is a 1999 ensemble crime-comedy film known for its interlocking stories, fast-paced narrative, and energetic depiction of a wild night involving drugs, raves, and misadventures.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: GO Triple: [Province of Gorizia, vehicleRegistrationCode, GO]
Generated description
GO is the vehicle registration code used on license plates for vehicles registered in the Province of Gorizia in northeastern Italy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GO Target entity description: GO is the vehicle registration code used on license plates for vehicles registered in the Province of Gorizia in northeastern Italy.
-
A.
Go
Go is an ancient East Asian abstract strategy board game, renowned for its simple rules yet immense strategic depth, played on a grid with black and white stones.
-
B.
Go
Go is a 1961 hard bop jazz album by bassist Paul Chambers, showcasing his work as a bandleader with a small ensemble.
-
C.
Go
Go is a statically typed, compiled programming language developed at Google, known for its simplicity, efficient concurrency support, and suitability for scalable networked and cloud services.
-
D.
Go
"Go" is a surf rock song, likely characterized by upbeat rhythms and guitar-driven melodies typical of the genre.
-
E.
Go
Go is a 1999 ensemble crime-comedy film known for its interlocking stories, fast-paced narrative, and energetic depiction of a wild night involving drugs, raves, and misadventures.
- F. None of above. chosen
Provenance (5 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990a8be108190bad0021f95ce3a93 |
completed | April 11, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716e58cc48190afb46e8394227ab5 |
completed | May 3, 2026, 9:35 a.m. |
| NEDg | Description generation | batch_69f7179da5488190a10acadbf60ea470 |
completed | May 3, 2026, 9:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f71847e7308190ac6f59a7dcafa452 |
completed | May 3, 2026, 9:41 a.m. |
Created at: April 9, 2026, 9:29 p.m.