Triple
T9950198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palamoor |
E195309
|
entity |
| Predicate | historicalNameOf |
P65
|
FINISHED |
| Object | Mahbubnagar |
E37569
|
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: Mahbubnagar | Statement: [Palamoor, historicalNameOf, Mahbubnagar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mahbubnagar Context triple: [Palamoor, historicalNameOf, Mahbubnagar]
-
A.
Mahbubnagar
chosen
Mahbubnagar is a town and district headquarters in the Indian state of Telangana, known for its agricultural surroundings and proximity to major rivers and irrigation projects.
-
B.
Jangaon
Jangaon is a town and municipal center in the Indian state of Telangana, known for its location along key road and rail routes between Hyderabad and Warangal.
-
C.
Khammam
Khammam is a city in the Indian state of Telangana known for its historical forts, temples, and proximity to the Munneru River.
-
D.
Nandyal
Nandyal is a city in the Indian state of Andhra Pradesh, known as a commercial and administrative center in the Rayalaseema region.
-
E.
Bhimnagar
Bhimnagar is a settlement in the Indian state of Bihar known for its proximity to the Kosi River and the major Kosi Barrage infrastructure.
- 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_69ca82e96a108190932bd1fc4acd73a0 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb65a4e6c8190968192a24aad1b7d |
completed | April 2, 2026, 12:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23d5c6fdc81909b44d0b321201222 |
completed | April 5, 2026, 10:45 a.m. |
Created at: March 30, 2026, 8:45 p.m.