Triple
T14128348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonipat |
E340091
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
HR-10
HR-10 is the regional vehicle registration code assigned to motor vehicles registered in the Sonipat district of Haryana, India.
|
E1082235
|
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: HR-10 | Statement: [Sonipat, vehicleRegistrationCode, HR-10]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HR-10 Context triple: [Sonipat, vehicleRegistrationCode, HR-10]
-
A.
HR-08
HR-08 is the ISO 3166-2 regional code assigned to the Primorje-Gorski Kotar County in Croatia.
-
B.
H10
H10 is the shorthand name for Hilbert’s tenth problem, a famous decision problem in number theory concerning the solvability of Diophantine equations.
-
C.
MR-UR-100
MR-UR-100 was a Soviet intercontinental ballistic missile (ICBM) system developed during the Cold War as part of the USSR’s strategic nuclear forces.
-
D.
TX-10
TX-10 is the commonly used abbreviation for Texas's 10th congressional district, a U.S. House of Representatives district covering parts of central Texas.
-
E.
FH10
FH10 is a proprietary vector graphics file format associated with Macromedia FreeHand version 10, used for storing illustrations and page layouts.
- 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: HR-10 Triple: [Sonipat, vehicleRegistrationCode, HR-10]
Generated description
HR-10 is the regional vehicle registration code assigned to motor vehicles registered in the Sonipat district of Haryana, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HR-10 Target entity description: HR-10 is the regional vehicle registration code assigned to motor vehicles registered in the Sonipat district of Haryana, India.
-
A.
HR-08
HR-08 is the ISO 3166-2 regional code assigned to the Primorje-Gorski Kotar County in Croatia.
-
B.
H10
H10 is the shorthand name for Hilbert’s tenth problem, a famous decision problem in number theory concerning the solvability of Diophantine equations.
-
C.
MR-UR-100
MR-UR-100 was a Soviet intercontinental ballistic missile (ICBM) system developed during the Cold War as part of the USSR’s strategic nuclear forces.
-
D.
TX-10
TX-10 is the commonly used abbreviation for Texas's 10th congressional district, a U.S. House of Representatives district covering parts of central Texas.
-
E.
FH10
FH10 is a proprietary vector graphics file format associated with Macromedia FreeHand version 10, used for storing illustrations and page layouts.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6098013c8190b1bac9d3fff60acd |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf0ed0a88190a7126887364fccdd |
completed | May 7, 2026, 6:50 p.m. |
| NEDg | Description generation | batch_69fce0cc78e881909090ac42a97ebb12 |
completed | May 7, 2026, 6:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fce1f53a8881909fd1258729a9879d |
completed | May 7, 2026, 7:03 p.m. |
Created at: April 9, 2026, 10:22 p.m.