Triple
T17132463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Digha |
E415754
|
entity |
| Predicate | nearbyPlace |
P2064
|
FINISHED |
| Object |
Tajpur
Tajpur is a quiet seaside destination on the Bay of Bengal in West Bengal, India, known for its relatively untouched beach and tranquil atmosphere compared to busier nearby resorts.
|
E1252966
|
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: Tajpur | Statement: [Digha, nearbyPlace, Tajpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tajpur Context triple: [Digha, nearbyPlace, Tajpur]
-
A.
Karimabad
Karimabad is a picturesque town in northern Pakistan’s Hunza region, known for its stunning mountain scenery, historic forts, and role as a popular base for trekkers and tourists.
-
B.
Karimabad
Karimabad is a neighborhood in Karachi, Pakistan, known for its bustling markets and central urban location within the city.
-
C.
Saida Khera
Saida Khera is a village in Punjab, India, known in folklore as a setting linked to the legendary love story of Heer Ranjha.
-
D.
Shakargarh
Shakargarh is a town in Punjab, Pakistan, known for its agricultural surroundings and proximity to the border with India.
-
E.
Khoshbagh
Khoshbagh is a historic garden-cemetery complex in Murshidabad, West Bengal, known as the burial place of several Nawabs of Bengal.
- 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: Tajpur Triple: [Digha, nearbyPlace, Tajpur]
Generated description
Tajpur is a quiet seaside destination on the Bay of Bengal in West Bengal, India, known for its relatively untouched beach and tranquil atmosphere compared to busier nearby resorts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tajpur Target entity description: Tajpur is a quiet seaside destination on the Bay of Bengal in West Bengal, India, known for its relatively untouched beach and tranquil atmosphere compared to busier nearby resorts.
-
A.
Karimabad
Karimabad is a picturesque town in northern Pakistan’s Hunza region, known for its stunning mountain scenery, historic forts, and role as a popular base for trekkers and tourists.
-
B.
Karimabad
Karimabad is a neighborhood in Karachi, Pakistan, known for its bustling markets and central urban location within the city.
-
C.
Saida Khera
Saida Khera is a village in Punjab, India, known in folklore as a setting linked to the legendary love story of Heer Ranjha.
-
D.
Shakargarh
Shakargarh is a town in Punjab, Pakistan, known for its agricultural surroundings and proximity to the border with India.
-
E.
Khoshbagh
Khoshbagh is a historic garden-cemetery complex in Murshidabad, West Bengal, known as the burial place of several Nawabs of Bengal.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f02ba4cc8190b6f433e08e958d83 |
completed | April 18, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01414eca3c8190aeec22fab3b5e767 |
completed | May 11, 2026, 2:39 a.m. |
| NEDg | Description generation | batch_6a01423a771881908c2eaff14e335ee2 |
completed | May 11, 2026, 2:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01430b7e008190bc3366cc89564409 |
completed | May 11, 2026, 2:46 a.m. |
Created at: April 10, 2026, 5:36 a.m.