Triple
T11422317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delhi NCR |
E270654
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
NCR
NCR is the commonly used abbreviation for the National Capital Region encompassing Delhi and its surrounding urban areas in India.
|
E924559
|
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: NCR | Statement: [Delhi NCR, hasAbbreviation, NCR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NCR Context triple: [Delhi NCR, hasAbbreviation, NCR]
-
A.
NCR
NCR is the commonly used acronym for the National Capital Region of the Philippines, encompassing Metro Manila and serving as the country’s political, economic, and cultural center.
-
B.
NCR
NCR is an Indian Railways zone headquartered in Prayagraj that manages key rail routes across parts of Uttar Pradesh, Madhya Pradesh, Rajasthan, and Haryana.
-
C.
NCR Corporation
NCR Corporation is a global technology company best known for its point-of-sale systems, ATMs, and other financial and retail transaction solutions.
-
D.
Diebold
Diebold is a Germanic given name and surname, historically used as a variant of Theobald.
-
E.
NCP
NCP is the commonly used abbreviation for the National Contingency Plan, the U.S. federal framework for responding to oil spills and hazardous substance releases.
- 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: NCR Triple: [Delhi NCR, hasAbbreviation, NCR]
Generated description
NCR is the commonly used abbreviation for the National Capital Region encompassing Delhi and its surrounding urban areas in India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NCR Target entity description: NCR is the commonly used abbreviation for the National Capital Region encompassing Delhi and its surrounding urban areas in India.
-
A.
NCR
NCR is the commonly used acronym for the National Capital Region of the Philippines, encompassing Metro Manila and serving as the country’s political, economic, and cultural center.
-
B.
NCR
NCR is an Indian Railways zone headquartered in Prayagraj that manages key rail routes across parts of Uttar Pradesh, Madhya Pradesh, Rajasthan, and Haryana.
-
C.
NCR Corporation
NCR Corporation is a global technology company best known for its point-of-sale systems, ATMs, and other financial and retail transaction solutions.
-
D.
Diebold
Diebold is a Germanic given name and surname, historically used as a variant of Theobald.
-
E.
NCP
NCP is the commonly used abbreviation for the National Contingency Plan, the U.S. federal framework for responding to oil spills and hazardous substance releases.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d801b357e88190ace56d36a945688f |
completed | April 9, 2026, 7:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5b8a1e88c8190994bea88a0490e60 |
completed | April 20, 2026, 5:24 a.m. |
| NEDg | Description generation | batch_69e5c28d3824819097ff84cb4e13c923 |
completed | April 20, 2026, 6:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5c451c6c88190bcbb1f54ede35d29 |
completed | April 20, 2026, 6:14 a.m. |
Created at: April 8, 2026, 9:34 p.m.