Triple
T1638527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guntur |
E35413
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Vijayawada |
E36504
|
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: Vijayawada | Statement: [Guntur, locatedNear, Vijayawada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vijayawada Context triple: [Guntur, locatedNear, Vijayawada]
-
A.
Vijayawada
chosen
Vijayawada is a major commercial and cultural city in the Indian state of Andhra Pradesh, known as a key transportation hub and an important center for trade, education, and politics in the region.
-
B.
Kakinada
Kakinada is a coastal city in the Indian state of Andhra Pradesh, known for its port, seafood industry, and role as a regional commercial hub.
-
C.
Guntur
Guntur is a major city in the Indian state of Andhra Pradesh, known historically as an important administrative and commercial center in southeastern India.
-
D.
Hyderabad
Hyderabad is a major city in southern India known for its historic Charminar monument, rich Hyderabadi cuisine, and growing technology industry.
-
E.
Hyderabad
Hyderabad is a major city in the Sindh province of Pakistan, known for its historical significance, vibrant culture, and role as an important commercial and industrial center.
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a1ac46081909f10e793898a9911 |
completed | March 5, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69addf308fe4819093ac42f637929a5e |
completed | March 8, 2026, 8:42 p.m. |
Created at: March 4, 2026, 7:28 p.m.