Triple
T16138793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhiwani district |
E391598
|
entity |
| Predicate | legislativeAssemblyConstituencies |
P23217
|
FINISHED |
| Object | Loharu |
E969064
|
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: Loharu | Statement: [Bhiwani district, legislativeAssemblyConstituencies, Loharu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loharu Context triple: [Bhiwani district, legislativeAssemblyConstituencies, Loharu]
-
A.
Loharu
chosen
Loharu is a town in the Bhiwani district of Haryana, India, known for its railway junction and historical Loharu Fort.
-
B.
Lohaghat
Lohaghat is a small hill town and popular scenic destination in Uttarakhand’s Kumaon region, known for its tranquil atmosphere and views of the surrounding Himalayas.
-
C.
Chamkoria
Chamkoria is the former name of Borovets, one of Bulgaria’s oldest and most popular mountain ski resorts.
-
D.
Bhailsa
Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
-
E.
Nalhati
Nalhati is a town in the Birbhum district of West Bengal, India, known for its religious significance and regional marketplace.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a06e0988190b5cd62d422d058a2 |
completed | April 17, 2026, 11:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f83f6ac8190b9f18fe701a9b3ce |
completed | May 10, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:01 a.m.