Triple
T8187156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Delhi |
E191213
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Daryaganj
Daryaganj is a historic neighborhood in Old Delhi, India, known for its Sunday book market, publishing houses, and colonial-era architecture.
|
E718065
|
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: Daryaganj | Statement: [Central Delhi, contains, Daryaganj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daryaganj Context triple: [Central Delhi, contains, Daryaganj]
-
A.
Shastri Nagar
Shastri Nagar is a small settlement located on Great Nicobar Island in the Andaman and Nicobar Islands of India.
-
B.
Hanuman Nagar
Hanuman Nagar is a town near the India–Nepal border known for its proximity to the Koshi River as it flows from Nepal into India.
-
C.
Laxmi Nagar
Laxmi Nagar is a small settlement located on Great Nicobar Island in the Andaman and Nicobar Islands of India.
-
D.
Kamla Nagar
Kamla Nagar is a prominent residential and commercial neighborhood in North Delhi known for its bustling markets, student-centric culture, and proximity to the University of Delhi’s North Campus.
-
E.
Azadpur
Azadpur is a locality in North Delhi, India, known for its major wholesale fruit and vegetable market and connectivity via the Delhi Metro.
- 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: Daryaganj Triple: [Central Delhi, contains, Daryaganj]
Generated description
Daryaganj is a historic neighborhood in Old Delhi, India, known for its Sunday book market, publishing houses, and colonial-era architecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daryaganj Target entity description: Daryaganj is a historic neighborhood in Old Delhi, India, known for its Sunday book market, publishing houses, and colonial-era architecture.
-
A.
Shastri Nagar
Shastri Nagar is a small settlement located on Great Nicobar Island in the Andaman and Nicobar Islands of India.
-
B.
Hanuman Nagar
Hanuman Nagar is a town near the India–Nepal border known for its proximity to the Koshi River as it flows from Nepal into India.
-
C.
Laxmi Nagar
Laxmi Nagar is a small settlement located on Great Nicobar Island in the Andaman and Nicobar Islands of India.
-
D.
Kamla Nagar
Kamla Nagar is a prominent residential and commercial neighborhood in North Delhi known for its bustling markets, student-centric culture, and proximity to the University of Delhi’s North Campus.
-
E.
Azadpur
Azadpur is a locality in North Delhi, India, known for its major wholesale fruit and vegetable market and connectivity via the Delhi Metro.
- 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_69ca82c5b6948190a583c096fb0a6c71 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4d9e01208190842170abf62d9afb |
completed | March 31, 2026, 4:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cced7a109c819092d43d9e3cfc0706 |
completed | April 1, 2026, 10:03 a.m. |
| NEDg | Description generation | batch_69ccf09b827881908e7fd7e9ff251674 |
completed | April 1, 2026, 10:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd0579b6d08190a5c68d730e1c6284 |
completed | April 1, 2026, 11:46 a.m. |
Created at: March 30, 2026, 5:41 p.m.