Triple
T1298965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middle Andaman Island |
E27717
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Rampur
Rampur is a small settlement located on Middle Andaman Island in the Andaman and Nicobar Islands of India.
|
E227408
|
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: Rampur | Statement: [Middle Andaman Island, hasSettlement, Rampur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rampur Context triple: [Middle Andaman Island, hasSettlement, Rampur]
-
A.
Yamunanagar
Yamunanagar is an industrial city in the Indian state of Haryana, known for its plywood, paper, and metal industries and its proximity to the Yamuna River.
-
B.
Ambala
Ambala is a historic city and important military and transportation hub in the northern Indian state of Haryana.
-
C.
Gorakhpur
Gorakhpur is a prominent city in northern India known as a regional commercial, transportation, and cultural hub near the border with Nepal.
-
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.
Sheopur
Sheopur is a town and district headquarters in the northern part of the Indian state of Madhya Pradesh, known for its proximity to the Kuno National Park and its largely rural, agrarian surroundings.
- 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: Rampur Triple: [Middle Andaman Island, hasSettlement, Rampur]
Generated description
Rampur is a small settlement located on Middle Andaman Island in the Andaman and Nicobar Islands of India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rampur Target entity description: Rampur is a small settlement located on Middle Andaman Island in the Andaman and Nicobar Islands of India.
-
A.
Yamunanagar
Yamunanagar is an industrial city in the Indian state of Haryana, known for its plywood, paper, and metal industries and its proximity to the Yamuna River.
-
B.
Ambala
Ambala is a historic city and important military and transportation hub in the northern Indian state of Haryana.
-
C.
Gorakhpur
Gorakhpur is a prominent city in northern India known as a regional commercial, transportation, and cultural hub near the border with Nepal.
-
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.
Sheopur
Sheopur is a town and district headquarters in the northern part of the Indian state of Madhya Pradesh, known for its proximity to the Kuno National Park and its largely rural, agrarian surroundings.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c111a76c81909e6b914694986251 |
completed | March 1, 2026, 10:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1fae5aa08190b6aa50b543a175b8 |
completed | March 9, 2026, 1:17 a.m. |
| NEDg | Description generation | batch_69ae204fe6148190915219beb27128bc |
completed | March 9, 2026, 1:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae20d09c748190aebbfb88f0eedbaa |
completed | March 9, 2026, 1:22 a.m. |
Created at: March 1, 2026, 7:51 p.m.