Triple
T21992491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uttar Pradesh |
E509513
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Ghaziabad |
—
|
NE NERFINISHED |
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: Ghaziabad | Statement: [Uttar Pradesh, containsCity, Ghaziabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ghaziabad Context triple: [Uttar Pradesh, containsCity, Ghaziabad]
-
A.
Ghaziabad
chosen
Ghaziabad is a major industrial and residential city in the Indian state of Uttar Pradesh, forming part of the National Capital Region near Delhi.
-
B.
Ghaziabad
Ghaziabad is a village located in the scenic Jhelum Valley region of Azad Jammu and Kashmir, Pakistan.
-
C.
Meerut
Meerut is a historic city in the Indian state of Uttar Pradesh, known as the place where the Indian Rebellion of 1857 first erupted against British colonial rule.
-
D.
Gautam Nagar
Gautam Nagar is a residential locality in South Delhi, India, known for its proximity to major institutions like AIIMS and Safdarjung Hospital.
-
E.
Faridabad
Faridabad is a major industrial city in northern India known for its manufacturing sector and its location within the National Capital Region near New Delhi.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1270e951081908deda039b47ca84b |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:15 p.m.