Triple
T14293900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LB Nagar |
E354387
|
entity |
| Predicate | nearbyArea |
P2064
|
FINISHED |
| Object |
Kothapet
Kothapet is a residential and commercial neighborhood in Hyderabad, Telangana, known for its markets, connectivity, and proximity to major city hubs.
|
E1104958
|
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: Kothapet | Statement: [LB Nagar, nearbyArea, Kothapet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kothapet Context triple: [LB Nagar, nearbyArea, Kothapet]
-
A.
Nandipet
Nandipet is a village located in the Nizamabad district of the Indian state of Telangana.
-
B.
Tadipatri
Tadipatri is a town in the Anantapur district of Andhra Pradesh, India, known for its granite industries and historic temples.
-
C.
Jaggayyapeta
Jaggayyapeta is a town and assembly constituency in the NTR district of Andhra Pradesh, India, known for its historical Buddhist sites and cement industries.
-
D.
Narayanavanam
Narayanavanam is a small town in the Tirupati district of Andhra Pradesh, India, known for its historic temples and religious significance.
-
E.
Sullurpeta
Sullurpeta is a town in Andhra Pradesh, India, known primarily for its proximity to India’s premier spaceport, the Satish Dhawan Space Centre at Sriharikota.
- 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: Kothapet Triple: [LB Nagar, nearbyArea, Kothapet]
Generated description
Kothapet is a residential and commercial neighborhood in Hyderabad, Telangana, known for its markets, connectivity, and proximity to major city hubs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kothapet Target entity description: Kothapet is a residential and commercial neighborhood in Hyderabad, Telangana, known for its markets, connectivity, and proximity to major city hubs.
-
A.
Nandipet
Nandipet is a village located in the Nizamabad district of the Indian state of Telangana.
-
B.
Tadipatri
Tadipatri is a town in the Anantapur district of Andhra Pradesh, India, known for its granite industries and historic temples.
-
C.
Jaggayyapeta
Jaggayyapeta is a town and assembly constituency in the NTR district of Andhra Pradesh, India, known for its historical Buddhist sites and cement industries.
-
D.
Narayanavanam
Narayanavanam is a small town in the Tirupati district of Andhra Pradesh, India, known for its historic temples and religious significance.
-
E.
Sullurpeta
Sullurpeta is a town in Andhra Pradesh, India, known primarily for its proximity to India’s premier spaceport, the Satish Dhawan Space Centre at Sriharikota.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de7179368081908117a9ccfbf94fd4 |
completed | April 14, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a3479088190929ab4b9d218a608 |
completed | May 8, 2026, 5:52 a.m. |
| NEDg | Description generation | batch_69fd7d80d358819095661dac316ff69f |
completed | May 8, 2026, 6:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd7e0a30188190942ff45e0f865490 |
completed | May 8, 2026, 6:09 a.m. |
Created at: April 10, 2026, 1:11 a.m.