Triple
T16111898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aligarh district |
E390898
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Khurja
Khurja is a town in Uttar Pradesh, India, renowned for its traditional ceramic and pottery industry.
|
E1224261
|
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: Khurja | Statement: [Aligarh district, containsTown, Khurja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khurja Context triple: [Aligarh district, containsTown, Khurja]
-
A.
Saharanpur
Saharanpur is a city in the Indian state of Uttar Pradesh known as a commercial and transportation hub, particularly for its wood carving industry and agricultural trade.
-
B.
Jaunsar-Bawar
Jaunsar-Bawar is a hilly, culturally distinct region in Uttarakhand, India, known for its Jaunsari-speaking communities, traditional architecture, and unique customs.
-
C.
Shahjahanpur
Shahjahanpur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known for its historical significance and regional commercial importance.
-
D.
Moradabad
Moradabad is a major city in northern India known for its brass handicraft industry and is located in the state of Uttar Pradesh.
-
E.
Ambala
Ambala is a historic city and important military and transportation hub in the northern Indian state of Haryana.
- 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: Khurja Triple: [Aligarh district, containsTown, Khurja]
Generated description
Khurja is a town in Uttar Pradesh, India, renowned for its traditional ceramic and pottery industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Khurja Target entity description: Khurja is a town in Uttar Pradesh, India, renowned for its traditional ceramic and pottery industry.
-
A.
Saharanpur
Saharanpur is a city in the Indian state of Uttar Pradesh known as a commercial and transportation hub, particularly for its wood carving industry and agricultural trade.
-
B.
Jaunsar-Bawar
Jaunsar-Bawar is a hilly, culturally distinct region in Uttarakhand, India, known for its Jaunsari-speaking communities, traditional architecture, and unique customs.
-
C.
Shahjahanpur
Shahjahanpur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known for its historical significance and regional commercial importance.
-
D.
Moradabad
Moradabad is a major city in northern India known for its brass handicraft industry and is located in the state of Uttar Pradesh.
-
E.
Ambala
Ambala is a historic city and important military and transportation hub in the northern Indian state of Haryana.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20167ee1481909e56dc632bfc0fc5 |
completed | April 17, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007d9849a08190a575f19e816e6df2 |
completed | May 10, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_6a007ec876ac8190afae26442f8b2a9a |
completed | May 10, 2026, 12:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a007f3bf6e081908554238d069d9abc |
completed | May 10, 2026, 12:51 p.m. |
Created at: April 10, 2026, 5 a.m.