Triple
T686060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ravi River |
E13285
|
entity |
| Predicate | historicalRegion |
P915
|
FINISHED |
| Object | Punjab |
E2323
|
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: Punjab | Statement: [Ravi River, historicalRegion, Punjab]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Punjab Context triple: [Ravi River, historicalRegion, Punjab]
-
A.
Punjab
chosen
Punjab is a historically and culturally rich region of South Asia, known for its fertile agricultural lands, Sikh heritage, and partition between modern-day India and Pakistan.
-
B.
Haryana
Haryana is a northern Indian state known for its significant agricultural output, rapid industrial growth, and proximity to the national capital, New Delhi.
-
C.
Sindh
Sindh is a southeastern province of Pakistan known for its historical Indus Valley heritage, major cities like Karachi and Hyderabad, and a rich Sindhi cultural and linguistic tradition.
-
D.
Uttar Pradesh
Uttar Pradesh is a populous northern Indian state known for its political influence, rich cultural and religious heritage, and historic cities such as Varanasi and Agra.
-
E.
Himachal Pradesh
Himachal Pradesh is a mountainous state in northern India known for its Himalayan landscapes, hill stations, and tourism.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0924dec8190bbbd2bb244f85211 |
completed | March 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c7074cc88190912969a1ba0a8c6e |
completed | March 4, 2026, 5:45 a.m. |
Created at: March 1, 2026, 7:36 p.m.