Triple
T14259026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ranga Reddy district |
E353461
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Shamshabad |
E353956
|
NE FINISHED |
How this triple was built (2 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: Shamshabad | Statement: [Ranga Reddy district, hasCity, Shamshabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shamshabad Context triple: [Ranga Reddy district, hasCity, Shamshabad]
-
A.
Shamshabad
chosen
Shamshabad is a suburban area near Hyderabad in the Indian state of Telangana, known primarily for hosting the Rajiv Gandhi International Airport.
-
B.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
-
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.
Muhammadabad
Muhammadabad is a town located in the Ghazipur district of the Indian state of Uttar Pradesh.
-
E.
Nasirabad
Nasirabad is a village in the Lower Hunza region of northern Pakistan, known for its mountainous terrain and proximity to the Karakoram Range.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6352611c819090d062fe3079cd03 |
completed | April 14, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d150b188190a0858ab94f81d9a8 |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 10, 2026, 1:09 a.m.