Triple
T3992209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ledo, Assam, India |
E87016
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Margherita, Assam
Margherita, Assam is a town in the Tinsukia district of northeastern India known historically for its coal mining and tea gardens.
|
E403756
|
NE FINISHED |
How this triple was built (4 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: Margherita, Assam | Statement: [Ledo, Assam, India, near, Margherita, Assam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margherita, Assam Context triple: [Ledo, Assam, India, near, Margherita, Assam]
-
A.
Naihati
Naihati is a town in West Bengal, India, known as the birthplace of renowned Bengali novelist and nationalist Bankim Chandra Chattopadhyay.
-
B.
Tamluk
Tamluk is a historic town in eastern India known as an ancient port city and administrative center in the Purba Medinipur district of West Bengal.
-
C.
Jalpaiguri
Jalpaiguri is a town in northeastern India known as an important administrative and commercial center near the Himalayan foothills.
-
D.
Benipur
Benipur is a town in the Darbhanga region of the Indian state of Bihar, known as a local center of trade and daily commerce.
-
E.
Tinsukia
Tinsukia is a town in Assam, India, known as a commercial hub of the region and a gateway to nearby wildlife-rich areas such as Dibru-Saikhowa National Park.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Margherita, Assam Triple: [Ledo, Assam, India, near, Margherita, Assam]
Generated description
Margherita, Assam is a town in the Tinsukia district of northeastern India known historically for its coal mining and tea gardens.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Margherita, Assam Target entity description: Margherita, Assam is a town in the Tinsukia district of northeastern India known historically for its coal mining and tea gardens.
-
A.
Naihati
Naihati is a town in West Bengal, India, known as the birthplace of renowned Bengali novelist and nationalist Bankim Chandra Chattopadhyay.
-
B.
Tamluk
Tamluk is a historic town in eastern India known as an ancient port city and administrative center in the Purba Medinipur district of West Bengal.
-
C.
Jalpaiguri
Jalpaiguri is a town in northeastern India known as an important administrative and commercial center near the Himalayan foothills.
-
D.
Benipur
Benipur is a town in the Darbhanga region of the Indian state of Bihar, known as a local center of trade and daily commerce.
-
E.
Tinsukia
Tinsukia is a town in Assam, India, known as a commercial hub of the region and a gateway to nearby wildlife-rich areas such as Dibru-Saikhowa National Park.
- F. None of above. chosen
Provenance (5 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa1c476c819094063f654aa015c4 |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54035e92c81909dc2be18719b062c |
completed | March 14, 2026, 11:02 a.m. |
| NEDg | Description generation | batch_69b541c668188190b5579e113149ddf5 |
completed | March 14, 2026, 11:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b54266cf908190848a51e20739441f |
completed | March 14, 2026, 11:11 a.m. |
Created at: March 9, 2026, 3:33 p.m.