Triple
T890307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maharashtra |
E19223
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Satara |
E58486
|
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: Satara | Statement: [Maharashtra, hasCity, Satara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Satara Context triple: [Maharashtra, hasCity, Satara]
-
A.
Satara
chosen
Satara is a historic city in the Indian state of Maharashtra, known for its role as a key political and cultural center of the Maratha dynasty.
-
B.
Titisee-Neustadt
Titisee-Neustadt is a popular resort town in Germany’s Black Forest region, known for its scenic lake Titisee, winter sports facilities, and tourism.
-
C.
Kanesville
Kanesville was the mid-19th-century Mormon settlement that later became the city of Council Bluffs, Iowa.
-
D.
Woodfin
Woodfin is the surname of Randall Woodfin, an American politician and mayor of Birmingham, Alabama.
-
E.
Tubas
Tubas is a Palestinian city in the northeastern West Bank, serving as the administrative center of the Tubas Governorate and known for its agricultural surroundings in the Jordan Valley region.
- 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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad0086a081908c47c285896a1f3c |
completed | March 1, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c023464481909759c457e87266ab |
completed | March 4, 2026, 5:16 a.m. |
Created at: March 1, 2026, 7:39 p.m.