Triple
T14047378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vandalur |
E337992
|
entity |
| Predicate | hasNearbyLocality |
P3883
|
FINISHED |
| Object |
Urapakkam
Urapakkam is a rapidly developing suburban residential area on the outskirts of Chennai in Tamil Nadu, India.
|
E1076172
|
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: Urapakkam | Statement: [Vandalur, hasNearbyLocality, Urapakkam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Urapakkam Context triple: [Vandalur, hasNearbyLocality, Urapakkam]
-
A.
Sattenapalle
Sattenapalle is a town in the Indian state of Andhra Pradesh, known as a local commercial and administrative center within the Guntur region.
-
B.
Gunamala
Gunamala is a concise Assamese devotional scripture that encapsulates the essence of the Bhagavata Purana, composed by the saint-scholar Srimanta Sankardev.
-
C.
Nannilam
Nannilam is a small town in the Tiruvarur district of Tamil Nadu, India, known for its traditional Tamil culture and rural setting.
-
D.
Vandiyur
Vandiyur is a locality in Madurai, Tamil Nadu, known for its historic temple tank and religious significance.
-
E.
Velaikkari
Velaikkari is a landmark Tamil play (later adapted into a film) written by C. N. Annadurai that powerfully combined social reform themes with Dravidian political ideology.
- 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: Urapakkam Triple: [Vandalur, hasNearbyLocality, Urapakkam]
Generated description
Urapakkam is a rapidly developing suburban residential area on the outskirts of Chennai in Tamil Nadu, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Urapakkam Target entity description: Urapakkam is a rapidly developing suburban residential area on the outskirts of Chennai in Tamil Nadu, India.
-
A.
Sattenapalle
Sattenapalle is a town in the Indian state of Andhra Pradesh, known as a local commercial and administrative center within the Guntur region.
-
B.
Gunamala
Gunamala is a concise Assamese devotional scripture that encapsulates the essence of the Bhagavata Purana, composed by the saint-scholar Srimanta Sankardev.
-
C.
Nannilam
Nannilam is a small town in the Tiruvarur district of Tamil Nadu, India, known for its traditional Tamil culture and rural setting.
-
D.
Vandiyur
Vandiyur is a locality in Madurai, Tamil Nadu, known for its historic temple tank and religious significance.
-
E.
Velaikkari
Velaikkari is a landmark Tamil play (later adapted into a film) written by C. N. Annadurai that powerfully combined social reform themes with Dravidian political ideology.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c88b5e48190b0f0149102c08992 |
completed | April 14, 2026, 1:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc34332448190b044f55f0f85d5e2 |
completed | May 6, 2026, 10:40 p.m. |
| NEDg | Description generation | batch_69fc43623d608190bee3ebd08ffa01e6 |
completed | May 7, 2026, 7:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fc43e71f708190903a63388b664ba5 |
completed | May 7, 2026, 7:48 a.m. |
Created at: April 9, 2026, 10:20 p.m.