Triple
T22458930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malappuram district |
E555180
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object |
Tavanur
Tavanur is a town in the Malappuram district of Kerala, India, known for its scenic location along the Bharathapuzha River and its educational institutions.
|
E1538255
|
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: Tavanur | Statement: [Malappuram district, hasMajorTown, Tavanur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tavanur Context triple: [Malappuram district, hasMajorTown, Tavanur]
-
A.
Tafas
Tafas is a town in southern Syria located in the Daraa Governorate, known for its agricultural surroundings and its role in regional events during the Syrian conflict.
-
B.
Tibarg
Tibarg is the central shopping and main thoroughfare of the Hamburg district Niendorf, known for its retail stores and local amenities.
-
C.
Tamsalu
Tamsalu is a small town in northern Estonia known for its historical railway connections and location within Lääne-Viru County.
-
D.
Tilarán
Tilarán is a small town in northwestern Costa Rica known as a gateway to the Monteverde region and nearby highland landscapes.
-
E.
Teteven
Teteven is a picturesque town in central Bulgaria, known for its mountainous scenery, rivers, and role as a regional cultural and tourist center.
- 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: Tavanur Triple: [Malappuram district, hasMajorTown, Tavanur]
Generated description
Tavanur is a town in the Malappuram district of Kerala, India, known for its scenic location along the Bharathapuzha River and its educational institutions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tavanur Target entity description: Tavanur is a town in the Malappuram district of Kerala, India, known for its scenic location along the Bharathapuzha River and its educational institutions.
-
A.
Tafas
Tafas is a town in southern Syria located in the Daraa Governorate, known for its agricultural surroundings and its role in regional events during the Syrian conflict.
-
B.
Tibarg
Tibarg is the central shopping and main thoroughfare of the Hamburg district Niendorf, known for its retail stores and local amenities.
-
C.
Tamsalu
Tamsalu is a small town in northern Estonia known for its historical railway connections and location within Lääne-Viru County.
-
D.
Tilarán
Tilarán is a small town in northwestern Costa Rica known as a gateway to the Monteverde region and nearby highland landscapes.
-
E.
Teteven
Teteven is a picturesque town in central Bulgaria, known for its mountainous scenery, rivers, and role as a regional cultural and tourist center.
- 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_69e11e51fdec8190adfdf9f8a6362221 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b7e01fc8190825c3dc024484440 |
completed | April 29, 2026, 1:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b1252beac81908238e7f6eda2c638 |
completed | May 18, 2026, 1:21 p.m. |
| NEDg | Description generation | batch_6a0b13cb589081909443d2f48e0384a2 |
completed | May 18, 2026, 1:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b14a5f8ec8190bd30684a82cf5b6e |
completed | May 18, 2026, 1:31 p.m. |
Created at: April 16, 2026, 8:48 p.m.