Triple
T8838652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sepang |
E210329
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Cyberjaya technology hub |
E272596
|
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: Cyberjaya technology hub | Statement: [Sepang, knownFor, Cyberjaya technology hub]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cyberjaya technology hub Context triple: [Sepang, knownFor, Cyberjaya technology hub]
-
A.
Cyberjaya
chosen
Cyberjaya is a planned smart city in Malaysia known as a major technology and innovation hub, hosting numerous IT companies, startups, and educational institutions.
-
B.
Cidade da Tecnologia
Cidade da Tecnologia is a nickname for Campina Grande, a Brazilian city renowned as a major regional hub for technology, innovation, and higher education.
-
C.
Putrajaya
Putrajaya is Malaysia’s planned federal administrative capital, known for its modern architecture, landscaped boulevards, and numerous government complexes.
-
D.
Cyberabad
Cyberabad is a popular moniker for the technology-driven, IT and software hub aspects of Hyderabad, India.
-
E.
Laguna Technopark
Laguna Technopark is a major industrial and economic zone in Laguna, Philippines, hosting numerous manufacturing and technology companies and serving as a key driver of regional development.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc606c60ac8190b2b6bd7f042c02f8 |
completed | April 1, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf89933e8c81909672bcec70f7d5ce |
completed | April 3, 2026, 9:34 a.m. |
Created at: March 30, 2026, 6:48 p.m.