Triple
T23496587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kolathunadu |
E571720
|
entity |
| Predicate | hadImportantTown |
P22141
|
FINISHED |
| Object |
Taliparamba
Taliparamba is a historic town in the Kannur district of Kerala, India, known for its ancient temples and role as a cultural and commercial center in the region.
|
E1588941
|
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: Taliparamba | Statement: [Kolathunadu, hadImportantTown, Taliparamba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taliparamba Context triple: [Kolathunadu, hadImportantTown, Taliparamba]
-
A.
Muvattupuzha
Muvattupuzha is a town in the Indian state of Kerala known as a commercial and transportation hub at the confluence of three rivers.
-
B.
Mattoor
Mattoor is a locality in the Indian state of Kerala known for housing the historic Thiru Vellaman Thulli Siva Temple.
-
C.
Mookkannoor
Mookkannoor is a village in Kerala, India, known for its agrarian landscape and proximity to the town of Aluva in Ernakulam district.
-
D.
Marayoor
Marayoor is a scenic village in Kerala, India, renowned for its natural sandalwood forests, prehistoric dolmens, and sugarcane farms near the Western Ghats.
-
E.
Panambi
Panambi is a city in southern Brazil known for its strong German-Brazilian cultural heritage and traditions.
- 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: Taliparamba Triple: [Kolathunadu, hadImportantTown, Taliparamba]
Generated description
Taliparamba is a historic town in the Kannur district of Kerala, India, known for its ancient temples and role as a cultural and commercial center in the region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taliparamba Target entity description: Taliparamba is a historic town in the Kannur district of Kerala, India, known for its ancient temples and role as a cultural and commercial center in the region.
-
A.
Muvattupuzha
Muvattupuzha is a town in the Indian state of Kerala known as a commercial and transportation hub at the confluence of three rivers.
-
B.
Mattoor
Mattoor is a locality in the Indian state of Kerala known for housing the historic Thiru Vellaman Thulli Siva Temple.
-
C.
Mookkannoor
Mookkannoor is a village in Kerala, India, known for its agrarian landscape and proximity to the town of Aluva in Ernakulam district.
-
D.
Marayoor
Marayoor is a scenic village in Kerala, India, renowned for its natural sandalwood forests, prehistoric dolmens, and sugarcane farms near the Western Ghats.
-
E.
Panambi
Panambi is a city in southern Brazil known for its strong German-Brazilian cultural heritage and traditions.
- 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7e00384819092729319a378d4ab |
completed | April 29, 2026, 6:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c8271bd388190acc97e26e5c142f8 |
completed | May 19, 2026, 3:32 p.m. |
| NEDg | Description generation | batch_6a0ca6f229308190bf72b52fd44144d3 |
completed | May 19, 2026, 6:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ca7f09af48190b7bfdae25d2f286b |
completed | May 19, 2026, 6:12 p.m. |
Created at: April 17, 2026, 6:05 p.m.