Triple
T8202701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zoho Corporation |
E191615
|
entity |
| Predicate | hasOfficeIn |
P1268
|
FINISHED |
| Object |
Tenkasi
Tenkasi is a town in the Indian state of Tamil Nadu, known for its scenic Western Ghats backdrop, historic temples, and growing role as an emerging technology hub.
|
E778511
|
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: Tenkasi | Statement: [Zoho Corporation, hasOfficeIn, Tenkasi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tenkasi Context triple: [Zoho Corporation, hasOfficeIn, Tenkasi]
-
A.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
B.
Rinshunkaku
Rinshunkaku is a historic Japanese-style pavilion located within Yokohama’s Sankeien Garden, known for its traditional architecture and scenic setting.
-
C.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
D.
Sankashū
Sankashū is a renowned anthology of waka poetry by the Japanese poet-monk Saigyō, celebrated for its deeply reflective and nature-focused verse from the late Heian period.
-
E.
Gotemba
Gotemba is a Japanese city in Shizuoka Prefecture known as a gateway to Mount Fuji and a popular base for outdoor activities and outlet shopping.
- 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: Tenkasi Triple: [Zoho Corporation, hasOfficeIn, Tenkasi]
Generated description
Tenkasi is a town in the Indian state of Tamil Nadu, known for its scenic Western Ghats backdrop, historic temples, and growing role as an emerging technology hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tenkasi Target entity description: Tenkasi is a town in the Indian state of Tamil Nadu, known for its scenic Western Ghats backdrop, historic temples, and growing role as an emerging technology hub.
-
A.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
B.
Rinshunkaku
Rinshunkaku is a historic Japanese-style pavilion located within Yokohama’s Sankeien Garden, known for its traditional architecture and scenic setting.
-
C.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
D.
Sankashū
Sankashū is a renowned anthology of waka poetry by the Japanese poet-monk Saigyō, celebrated for its deeply reflective and nature-focused verse from the late Heian period.
-
E.
Gotemba
Gotemba is a Japanese city in Shizuoka Prefecture known as a gateway to Mount Fuji and a popular base for outdoor activities and outlet shopping.
- 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_69ca82c7f3e08190857bf1fc63b2a10c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5df84b108190b4407a72a3500af9 |
completed | March 31, 2026, 5:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d02f2a6ca88190b3f234447feab6e3 |
completed | April 3, 2026, 9:20 p.m. |
| NEDg | Description generation | batch_69d03133ab2081909ea8d32bd7689dec |
completed | April 3, 2026, 9:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d031db52d08190962c352014a99135 |
completed | April 3, 2026, 9:32 p.m. |
Created at: March 30, 2026, 5:43 p.m.