Triple
T9770757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hailakandi district |
E237116
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Algapur
Algapur is a small town in the Hailakandi district of the Indian state of Assam.
|
E820052
|
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: Algapur | Statement: [Hailakandi district, hasTown, Algapur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Algapur Context triple: [Hailakandi district, hasTown, Algapur]
-
A.
Partapur
Partapur is a locality in Meerut district of Uttar Pradesh, India, known for its proximity to the Dr. Bhimrao Ambedkar Airstrip and its growing urban and institutional development.
-
B.
Jwalapur
Jwalapur is a prominent suburban town and commercial hub near Haridwar in the Indian state of Uttarakhand.
-
C.
Brahmapuri
Brahmapuri is a town in Maharashtra, India, known as one of the important urban centers within Chandrapur district.
-
D.
Sohagpur
Sohagpur is a town in the Narmadapuram district of Madhya Pradesh, India, known as a local commercial center and access point to nearby forested and wildlife areas.
-
E.
Gajsinghpur
Gajsinghpur is a small town in the northern Indian state of Rajasthan, near the India–Pakistan border, known primarily as a local agricultural and trading center.
- 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: Algapur Triple: [Hailakandi district, hasTown, Algapur]
Generated description
Algapur is a small town in the Hailakandi district of the Indian state of Assam.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Algapur Target entity description: Algapur is a small town in the Hailakandi district of the Indian state of Assam.
-
A.
Partapur
Partapur is a locality in Meerut district of Uttar Pradesh, India, known for its proximity to the Dr. Bhimrao Ambedkar Airstrip and its growing urban and institutional development.
-
B.
Jwalapur
Jwalapur is a prominent suburban town and commercial hub near Haridwar in the Indian state of Uttarakhand.
-
C.
Brahmapuri
Brahmapuri is a town in Maharashtra, India, known as one of the important urban centers within Chandrapur district.
-
D.
Sohagpur
Sohagpur is a town in the Narmadapuram district of Madhya Pradesh, India, known as a local commercial center and access point to nearby forested and wildlife areas.
-
E.
Gajsinghpur
Gajsinghpur is a small town in the northern Indian state of Rajasthan, near the India–Pakistan border, known primarily as a local agricultural and trading center.
- 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_69ca84d831b8819090322686b47887ce |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda0f1dea08190b89bcc192b068c66 |
completed | April 1, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bd0cae548190a2d9b42ea4ecc372 |
completed | April 5, 2026, 1:38 a.m. |
| NEDg | Description generation | batch_69d1be4f81cc819093a80da4025ccc5d |
completed | April 5, 2026, 1:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1beda84d4819089eb9f33824f1c35 |
completed | April 5, 2026, 1:46 a.m. |
Created at: March 30, 2026, 8:26 p.m.