Triple
T23485351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cham towers |
E570518
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Nha Trang |
—
|
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: Nha Trang | Statement: [Cham towers, locatedIn, Nha Trang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nha Trang Context triple: [Cham towers, locatedIn, Nha Trang]
-
A.
Nha Trang
chosen
Nha Trang is a coastal resort city in Vietnam renowned for its sandy beaches, scuba diving, and vibrant tourism industry.
-
B.
Da Nang
Da Nang is a major coastal city in central Vietnam known for its sandy beaches, modern infrastructure, and proximity to historic sites like Hoi An and the Marble Mountains.
-
C.
Phan Thiết
Phan Thiết is a coastal city in south-central Vietnam known for its fishing industry, beaches, and nearby resort area of Mũi Né.
-
D.
Tuy Hoa
Tuy Hoa is a coastal city in south-central Vietnam known for its beaches, rice fields, and role as the capital of Phú Yên Province.
-
E.
Pleiku
Pleiku is a city in Vietnam’s Central Highlands known as a regional hub for coffee production and as a strategic site during the Vietnam War.
- 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_69e245b0b01481908f636939bedd804c |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7538a8c8190b7effcc39a3f9787 |
completed | April 29, 2026, 6:38 a.m. |
Created at: April 17, 2026, 6:03 p.m.