Triple
T4015233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karnal district |
E90740
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Karnal |
E389853
|
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: Karnal | Statement: [Karnal district, hasCapital, Karnal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karnal Context triple: [Karnal district, hasCapital, Karnal]
-
A.
Karnal
chosen
Karnal is a historic city in the Indian state of Haryana, known for its agricultural significance and strategic location along the Grand Trunk Road between Delhi and Chandigarh.
-
B.
Barnala
Barnala is a city in the Malwa region of Punjab, India, known as an administrative and commercial center for the surrounding agricultural area.
-
C.
Nadiad
Nadiad is a city in the Indian state of Gujarat, historically notable as the birthplace of independence leader Sardar Vallabhbhai Patel.
-
D.
Nawanshahr
Nawanshahr is a town and district headquarters in the Doaba region of Punjab, India, known for its agricultural base and significant Punjabi diaspora.
-
E.
Randhawa
Randhawa is an Indian-origin Punjabi surname notably borne by American politician Nikki Haley.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaa5afdc8190b709af2473d75d02 |
completed | March 9, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b556295aa081908e803233b986fec9 |
completed | March 14, 2026, 12:35 p.m. |
Created at: March 9, 2026, 3:35 p.m.