Triple
T3059453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province 5 |
E60560
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Tulsipur
Tulsipur is a growing urban center in western Nepal known for its role as a commercial and transportation hub in the Dang District.
|
E321963
|
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: Tulsipur | Statement: [Province 5, hasMajorCity, Tulsipur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tulsipur Context triple: [Province 5, hasMajorCity, Tulsipur]
-
A.
Gorakhpur
Gorakhpur is a prominent city in northern India known as a regional commercial, transportation, and cultural hub near the border with Nepal.
-
B.
Bhagyanagar
Bhagyanagar is an old historical name for the Indian city now known as Hyderabad.
-
C.
Hazaribagh
Hazaribagh is a town in the Indian state of Jharkhand known for its scenic hills, pleasant climate, and proximity to Hazaribagh National Park.
-
D.
Rampur
Rampur is a small settlement located on Middle Andaman Island in the Andaman and Nicobar Islands of India.
-
E.
Rampur
Rampur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known historically for its princely state heritage and distinctive Rampuri culture.
- 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: Tulsipur Triple: [Province 5, hasMajorCity, Tulsipur]
Generated description
Tulsipur is a growing urban center in western Nepal known for its role as a commercial and transportation hub in the Dang District.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tulsipur Target entity description: Tulsipur is a growing urban center in western Nepal known for its role as a commercial and transportation hub in the Dang District.
-
A.
Gorakhpur
Gorakhpur is a prominent city in northern India known as a regional commercial, transportation, and cultural hub near the border with Nepal.
-
B.
Bhagyanagar
Bhagyanagar is an old historical name for the Indian city now known as Hyderabad.
-
C.
Hazaribagh
Hazaribagh is a town in the Indian state of Jharkhand known for its scenic hills, pleasant climate, and proximity to Hazaribagh National Park.
-
D.
Rampur
Rampur is a small settlement located on Middle Andaman Island in the Andaman and Nicobar Islands of India.
-
E.
Rampur
Rampur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known historically for its princely state heritage and distinctive Rampuri culture.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9e9cf9188190b43f50edc009030d |
completed | March 8, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1ef0b989c819094daaf222bf01d02 |
completed | March 11, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69b1efdd73188190b7a47fc2a1d627d1 |
completed | March 11, 2026, 10:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1f062abf48190ab891463c5b33622 |
completed | March 11, 2026, 10:44 p.m. |
Created at: March 8, 2026, 3:02 p.m.