Triple
T22701122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohanlalganj tehsil |
E561325
|
entity |
| Predicate | administrativeCentre |
P1474
|
FINISHED |
| Object |
Mohanlalganj
Mohanlalganj is a town in the Lucknow district of Uttar Pradesh, India, known primarily as a local administrative and market center for the surrounding rural region.
|
E1549847
|
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: Mohanlalganj | Statement: [Mohanlalganj tehsil, administrativeCentre, Mohanlalganj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mohanlalganj Context triple: [Mohanlalganj tehsil, administrativeCentre, Mohanlalganj]
-
A.
Mohanpur
Mohanpur is a settlement located within the Gaya district in the Indian state of Bihar.
-
B.
Sahibganj
Sahibganj is a town and district headquarters in Jharkhand, India, situated along the Ganges River and known as a regional rail and river transport hub.
-
C.
Maharajganj
Maharajganj is a city in the Purvanchal region of Uttar Pradesh, India, serving as an administrative and commercial center near the Indo-Nepal border.
-
D.
Sitarganj
Sitarganj is a town in the Udham Singh Nagar district of Uttarakhand, India, known for its agricultural surroundings and growing industrial development.
-
E.
Mahilpur
Mahilpur is a town in the Hoshiarpur district of Punjab, India, known for its educational institutions and local commerce.
- 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: Mohanlalganj Triple: [Mohanlalganj tehsil, administrativeCentre, Mohanlalganj]
Generated description
Mohanlalganj is a town in the Lucknow district of Uttar Pradesh, India, known primarily as a local administrative and market center for the surrounding rural region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mohanlalganj Target entity description: Mohanlalganj is a town in the Lucknow district of Uttar Pradesh, India, known primarily as a local administrative and market center for the surrounding rural region.
-
A.
Mohanpur
Mohanpur is a settlement located within the Gaya district in the Indian state of Bihar.
-
B.
Sahibganj
Sahibganj is a town and district headquarters in Jharkhand, India, situated along the Ganges River and known as a regional rail and river transport hub.
-
C.
Maharajganj
Maharajganj is a city in the Purvanchal region of Uttar Pradesh, India, serving as an administrative and commercial center near the Indo-Nepal border.
-
D.
Sitarganj
Sitarganj is a town in the Udham Singh Nagar district of Uttarakhand, India, known for its agricultural surroundings and growing industrial development.
-
E.
Mahilpur
Mahilpur is a town in the Hoshiarpur district of Punjab, India, known for its educational institutions and local commerce.
- 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_69e2454e615481909c177440be559d2c |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178cb2f548190bfc6f050be7c795a |
completed | April 29, 2026, 3:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b7ed1f220819084322d245405829f |
completed | May 18, 2026, 9:04 p.m. |
| NEDg | Description generation | batch_6a0b7f823bc481909b646fdc338fdbb7 |
completed | May 18, 2026, 9:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b8054938c8190a1e873fa6ef00a8b |
completed | May 18, 2026, 9:10 p.m. |
Created at: April 17, 2026, 3:15 p.m.