Triple
T9989590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urdu literature |
E196850
|
entity |
| Predicate | hasNotableWriter |
P10455
|
FINISHED |
| Object | Krishan Chander |
E748264
|
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: Krishan Chander | Statement: [Urdu literature, hasNotableWriter, Krishan Chander]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krishan Chander Context triple: [Urdu literature, hasNotableWriter, Krishan Chander]
-
A.
Krishan Chander
chosen
Krishan Chander was a prominent 20th-century Urdu and Hindi writer and satirist known for his socially conscious short stories and novels.
-
B.
Pradip Krishen
Pradip Krishen is an Indian filmmaker-turned-environmentalist and naturalist known for his documentaries and influential work on urban ecology and tree mapping in India.
-
C.
Haresh Chandra
Haresh Chandra is an individual known primarily in this context as the child of Rani Chandra.
-
D.
Inder Verma
Inder Verma is an Indian-American molecular biologist known for his pioneering work in gene therapy and cancer genetics.
-
E.
Ashok Chandra
Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
- 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_69ca82f1678c819093d06320a05f16a4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdc79f3df08190ab3094ad1cd5490f |
completed | April 2, 2026, 1:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d26a21b2388190b16f0aa142846599 |
completed | April 5, 2026, 1:56 p.m. |
Created at: March 30, 2026, 8:50 p.m.