Triple
T6304983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bareilly division |
E141351
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | UP |
E509513
|
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: UP | Statement: [Bareilly division, vehicleRegistrationCode, UP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UP Context triple: [Bareilly division, vehicleRegistrationCode, UP]
-
A.
UP
UP is the standard reporting mark used to identify rail equipment owned or operated by the Union Pacific Railroad in North America.
-
B.
UP
chosen
UP is the Indian state of Uttar Pradesh, the country’s most populous state and a major political and cultural center in northern India.
-
C.
UP
UP is a leading South African public research university located in Pretoria, known for its comprehensive range of academic programs and strong research output.
-
D.
Up
"Up" is a 2021 hip hop single by American rapper Cardi B known for its aggressive delivery, catchy hook, and viral popularity.
-
E.
Up
Up is a critically acclaimed 2009 Pixar animated film that follows an elderly widower and a young boy on a fantastical balloon-lifted house adventure, noted for its emotional depth and imaginative storytelling.
- 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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0645f26a881909d5746151c0843cc |
completed | March 22, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e44527488190b3d605e917c8dfb2 |
completed | March 27, 2026, 1:58 a.m. |
Created at: March 22, 2026, 4:28 p.m.