Triple
T14876064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khairatabad |
E349869
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Saifabad
Saifabad is a central locality in Hyderabad, India, known for its government offices and proximity to major administrative and commercial areas.
|
E1126005
|
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: Saifabad | Statement: [Khairatabad, near, Saifabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saifabad Context triple: [Khairatabad, near, Saifabad]
-
A.
Shamshabad
Shamshabad is a suburban area near Hyderabad in the Indian state of Telangana, known primarily for hosting the Rajiv Gandhi International Airport.
-
B.
Vikarabad
Vikarabad is a town in the Indian state of Telangana known for its nearby Ananthagiri Hills, a popular hill station and trekking destination.
-
C.
Sultanabad
Sultanabad is the former name of the Iranian city now known as Arak, an important industrial and historical center in central Iran.
-
D.
Nooriabad
Nooriabad is an industrial town in the Jamshoro District of Sindh, Pakistan, known for its manufacturing zones and proximity to Karachi.
-
E.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
- 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: Saifabad Triple: [Khairatabad, near, Saifabad]
Generated description
Saifabad is a central locality in Hyderabad, India, known for its government offices and proximity to major administrative and commercial areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saifabad Target entity description: Saifabad is a central locality in Hyderabad, India, known for its government offices and proximity to major administrative and commercial areas.
-
A.
Shamshabad
Shamshabad is a suburban area near Hyderabad in the Indian state of Telangana, known primarily for hosting the Rajiv Gandhi International Airport.
-
B.
Vikarabad
Vikarabad is a town in the Indian state of Telangana known for its nearby Ananthagiri Hills, a popular hill station and trekking destination.
-
C.
Sultanabad
Sultanabad is the former name of the Iranian city now known as Arak, an important industrial and historical center in central Iran.
-
D.
Nooriabad
Nooriabad is an industrial town in the Jamshoro District of Sindh, Pakistan, known for its manufacturing zones and proximity to Karachi.
-
E.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e3e5d48190a132f2cf012b01e2 |
completed | April 15, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b52c12481908d0173a2a3ed854b |
completed | May 8, 2026, 11:01 p.m. |
| NEDg | Description generation | batch_69fe6bf09424819095fa5b2e20e8d07d |
completed | May 8, 2026, 11:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe6c6ebe4881909334d772e45403f6 |
completed | May 8, 2026, 11:06 p.m. |
Created at: April 10, 2026, 1:55 a.m.