Triple
T15648225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banaskantha district |
E376236
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Danta
Danta is a town in the Banaskantha district of Gujarat, India, known for its historical and cultural significance in the region.
|
E1169434
|
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: Danta | Statement: [Banaskantha district, hasTown, Danta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danta Context triple: [Banaskantha district, hasTown, Danta]
-
A.
Dashanana
Dashanana is an epithet of the demon-king Ravana from the Hindu epic Ramayana, highlighting his legendary form with ten heads and immense power.
-
B.
Darganata
Darganata is a town in eastern Turkmenistan situated along the Amu Darya River in the Lebap Region.
-
C.
Dumarao
Dumarao is a municipality in the province of Capiz in the Western Visayas region of the Philippines, known for its predominantly agricultural economy and rural communities.
-
D.
Dara
Dara is a given name most prominently associated with Dara Khosrowshahi, the Iranian-American businessman and CEO of Uber.
-
E.
Dara
Dara was a strategically important fortified city in northern Mesopotamia that served as a key Byzantine stronghold against the Sasanian Empire.
- 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: Danta Triple: [Banaskantha district, hasTown, Danta]
Generated description
Danta is a town in the Banaskantha district of Gujarat, India, known for its historical and cultural significance in the region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Danta Target entity description: Danta is a town in the Banaskantha district of Gujarat, India, known for its historical and cultural significance in the region.
-
A.
Dashanana
Dashanana is an epithet of the demon-king Ravana from the Hindu epic Ramayana, highlighting his legendary form with ten heads and immense power.
-
B.
Darganata
Darganata is a town in eastern Turkmenistan situated along the Amu Darya River in the Lebap Region.
-
C.
Dumarao
Dumarao is a municipality in the province of Capiz in the Western Visayas region of the Philippines, known for its predominantly agricultural economy and rural communities.
-
D.
Dara
Dara is a given name most prominently associated with Dara Khosrowshahi, the Iranian-American businessman and CEO of Uber.
-
E.
Dara
Dara was a strategically important fortified city in northern Mesopotamia that served as a key Byzantine stronghold against the Sasanian Empire.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed7212c8190be6ff76afa25f7ca |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff67936e388190913c9060194e5b53 |
completed | May 9, 2026, 4:57 p.m. |
| NEDg | Description generation | batch_69ff6883b5048190b64e4361bc89dd80 |
completed | May 9, 2026, 5:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff6911a76c819088c8a86d2106b6c6 |
completed | May 9, 2026, 5:04 p.m. |
Created at: April 10, 2026, 4:15 a.m.