Triple
T9743660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chepauk |
E236251
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Egmore |
E336211
|
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: Egmore | Statement: [Chepauk, adjacentTo, Egmore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Egmore Context triple: [Chepauk, adjacentTo, Egmore]
-
A.
Egmore
chosen
Egmore is a prominent neighborhood in central Chennai, India, known as a major cultural, commercial, and transportation hub of the city.
-
B.
Tilehurst
Tilehurst is a suburban area and former village on the western edge of Reading in Berkshire, England, known for its residential character and proximity to the River Thames.
-
C.
Valsad
Valsad is a coastal city in southern Gujarat, India, known for its significant Parsi community, historical trading importance, and surrounding chikoo orchards.
-
D.
Zaman Town
Zaman Town is a residential neighborhood located within the Korangi District of Karachi, Pakistan.
-
E.
Shortlands
Shortlands is a suburban area in the London Borough of Bromley, known for its residential character and commuter links into central London.
- 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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f2e5bb081908047e3bf5fe3991c |
completed | April 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1affb761881908dde9a4f028c32f6 |
completed | April 5, 2026, 12:42 a.m. |
Created at: March 30, 2026, 8:23 p.m.