Triple
T14150546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nampally |
E350665
|
entity |
| Predicate | nearbyLandmark |
P350
|
FINISHED |
| Object |
Lakdikapul
Lakdikapul is a prominent commercial and transit locality in central Hyderabad, known for its busy roads, hotels, and connectivity to major city hubs.
|
E1091099
|
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: Lakdikapul | Statement: [Nampally, nearbyLandmark, Lakdikapul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakdikapul Context triple: [Nampally, nearbyLandmark, Lakdikapul]
-
A.
Partapur
Partapur is a locality in Meerut district of Uttar Pradesh, India, known for its proximity to the Dr. Bhimrao Ambedkar Airstrip and its growing urban and institutional development.
-
B.
Jwalapur
Jwalapur is a prominent suburban town and commercial hub near Haridwar in the Indian state of Uttarakhand.
-
C.
Karanpur
Karanpur is a town located in the Ganganagar district of the northern Indian state of Rajasthan.
-
D.
Vikrampura
Vikrampura was an important historical city that served as a principal royal center of the medieval Indian Pala dynasty in eastern India.
-
E.
Lakhisarai
Lakhisarai is a town and administrative district headquarters in the eastern Indian state of Bihar, known for its historical significance and role as a regional commercial center.
- 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: Lakdikapul Triple: [Nampally, nearbyLandmark, Lakdikapul]
Generated description
Lakdikapul is a prominent commercial and transit locality in central Hyderabad, known for its busy roads, hotels, and connectivity to major city hubs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lakdikapul Target entity description: Lakdikapul is a prominent commercial and transit locality in central Hyderabad, known for its busy roads, hotels, and connectivity to major city hubs.
-
A.
Partapur
Partapur is a locality in Meerut district of Uttar Pradesh, India, known for its proximity to the Dr. Bhimrao Ambedkar Airstrip and its growing urban and institutional development.
-
B.
Jwalapur
Jwalapur is a prominent suburban town and commercial hub near Haridwar in the Indian state of Uttarakhand.
-
C.
Karanpur
Karanpur is a town located in the Ganganagar district of the northern Indian state of Rajasthan.
-
D.
Vikrampura
Vikrampura was an important historical city that served as a principal royal center of the medieval Indian Pala dynasty in eastern India.
-
E.
Lakhisarai
Lakhisarai is a town and administrative district headquarters in the eastern Indian state of Bihar, known for its historical significance and role as a regional commercial center.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6124e23481909e5132a40a1d8624 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d043860819099526cbae1b1ef18 |
completed | May 8, 2026, 1:31 a.m. |
| NEDg | Description generation | batch_69fd3e13914c81908f4dcda7f0f6a927 |
completed | May 8, 2026, 1:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd3ee3f66081909301276aeee05350 |
completed | May 8, 2026, 1:39 a.m. |
Created at: April 10, 2026, 12:56 a.m.