Triple
T16872820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varthur Road |
E421216
|
entity |
| Predicate | hasNeighbourhoodAlong |
P16140
|
FINISHED |
| Object | Varthur |
E1239737
|
NE FINISHED |
How this triple was built (2 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: Varthur | Statement: [Varthur Road, hasNeighbourhoodAlong, Varthur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varthur Context triple: [Varthur Road, hasNeighbourhoodAlong, Varthur]
-
A.
Varthur
chosen
Varthur is a rapidly developing suburban neighborhood in the eastern part of Bengaluru, India, known for its residential complexes, tech parks, and proximity to major IT hubs like Whitefield.
-
B.
Vintar
Vintar is a landlocked agricultural municipality in the province of Ilocos Norte in the Philippines, known for its rural landscapes and river valleys.
-
C.
Atheras
Atheras is a mountainous region on the Greek island of Ikaria, known for its rugged terrain and scenic landscapes.
-
D.
Aternus
Aternus is an ancient river in central Italy historically associated with the territory of the Marrucini people.
-
E.
Vayentha
Vayentha is a ruthless assassin and primary antagonist in Dan Brown's novel and film adaptation "Inferno."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7f40410819088db22fa0d1eb808 |
completed | April 18, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfc6e77c8190853f747687299fce |
completed | May 10, 2026, 6:34 p.m. |
Created at: April 10, 2026, 5:29 a.m.