Triple
T22522091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pettah |
E556805
|
entity |
| Predicate | hasMarket |
P2714
|
FINISHED |
| Object | Pettah Market |
—
|
NE NERFINISHED |
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: Pettah Market | Statement: [Pettah, hasMarket, Pettah Market]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pettah Market Context triple: [Pettah, hasMarket, Pettah Market]
-
A.
Pettah
chosen
Pettah is a bustling commercial district in central Colombo, Sri Lanka, known for its crowded markets, wholesale trade, and vibrant street life.
-
B.
Đông Ba Market
Đông Ba Market is a large, historic central market in Huế, Vietnam, known for its bustling atmosphere and wide variety of local foods, handicrafts, and everyday goods.
-
C.
Queen’s Market
Queen’s Market is a bustling East London street market known for its diverse food stalls, fresh produce, and multicultural atmosphere.
-
D.
Hung Hom Market
Hung Hom Market is a local indoor wet market in Hong Kong’s Hung Hom district, offering fresh produce, meat, seafood, and daily necessities to neighborhood residents.
-
E.
Nakasero Market
Nakasero Market is a bustling open-air and covered marketplace in central Kampala, Uganda, known for its fresh produce, textiles, and everyday goods.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e5657e881909f16ca58352c50da |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e32b8a88190ac335d4298dd5ee3 |
completed | April 29, 2026, 1:26 a.m. |
Created at: April 16, 2026, 8:50 p.m.