Triple
T14259029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ranga Reddy district |
E353461
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Tandur
Tandur is a town in the Indian state of Telangana known for its limestone industries and stone quarries.
|
E1089780
|
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: Tandur | Statement: [Ranga Reddy district, hasCity, Tandur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tandur Context triple: [Ranga Reddy district, hasCity, Tandur]
-
A.
Tordino
Tordino is a river in the Abruzzo region of central Italy that flows through the city of Teramo before reaching the Adriatic Sea.
-
B.
Tunasan
Tunasan is a barangay and district in the southern part of Muntinlupa City in Metro Manila, Philippines.
-
C.
Tendaba
Tendaba is a small riverside village in The Gambia known as a key gateway and base for visiting Kiang West National Park and its surrounding wildlife areas.
-
D.
Tarusa
Tarusa is a small historic town in western Russia known for its scenic location on the Oka River and its associations with Russian artists and writers.
-
E.
Martos
Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
- 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: Tandur Triple: [Ranga Reddy district, hasCity, Tandur]
Generated description
Tandur is a town in the Indian state of Telangana known for its limestone industries and stone quarries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tandur Target entity description: Tandur is a town in the Indian state of Telangana known for its limestone industries and stone quarries.
-
A.
Tordino
Tordino is a river in the Abruzzo region of central Italy that flows through the city of Teramo before reaching the Adriatic Sea.
-
B.
Tunasan
Tunasan is a barangay and district in the southern part of Muntinlupa City in Metro Manila, Philippines.
-
C.
Tendaba
Tendaba is a small riverside village in The Gambia known as a key gateway and base for visiting Kiang West National Park and its surrounding wildlife areas.
-
D.
Tarusa
Tarusa is a small historic town in western Russia known for its scenic location on the Oka River and its associations with Russian artists and writers.
-
E.
Martos
Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
- 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_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_69fd3260fdf88190b482480a17bd6674 |
completed | May 8, 2026, 12:46 a.m. |
| NEDg | Description generation | batch_69fd33cba18481908f2dfe358017f11b |
completed | May 8, 2026, 12:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd346ffb9c81909ec28e514ea5451b |
completed | May 8, 2026, 12:55 a.m. |
Created at: April 10, 2026, 1:09 a.m.