Triple
T20821693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bareilly district |
E512589
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Aonla |
—
|
NE NERFINISHED |
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: Aonla | Statement: [Bareilly district, hasTown, Aonla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aonla Context triple: [Bareilly district, hasTown, Aonla]
-
A.
Aonla
chosen
Aonla is a parliamentary constituency in Uttar Pradesh, India, known for its agricultural economy and political significance.
-
B.
Amla
Amla is the surname of Hashim Amla, a renowned South African cricketer celebrated for his prolific batting and elegant technique.
-
C.
Amla
Amla is a town in the Betul district of Madhya Pradesh, India, known primarily as a regional railway and administrative center.
-
D.
Malvan
Malvan is a coastal town in Maharashtra, India, known for its beaches, seafood cuisine, and historic Sindhudurg Fort.
-
E.
Persea indica
Persea indica is an evergreen laurel tree native to the Macaronesian laurel forests, notable for its broad, glossy leaves and role as a dominant canopy species in humid subtropical woodlands.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2f7a1548190b6ef3f1cfad37c1c |
completed | April 21, 2026, 12:21 a.m. |
Created at: April 16, 2026, 12:41 p.m.