Triple
T5964209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Exponent |
E132712
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Expo |
E88623
|
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: Expo | Statement: [Exponent, product, Expo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Expo Context triple: [Exponent, product, Expo]
-
A.
Expo
chosen
Expo is a popular brand best known for its dry-erase markers and related whiteboard accessories commonly used in schools, offices, and homes.
-
B.
The Expo
The Expo is a well-known multipurpose event and exhibition venue in Portland, Oregon, hosting trade shows, conventions, and community events.
-
C.
Expo 85
Expo 85 was a world's fair held in Tsukuba, Japan, showcasing advances in science and technology during the mid-1980s.
-
D.
Expo 2020
Expo 2020 was a World Expo held in Dubai that showcased global innovation, culture, and sustainability through international pavilions and events.
-
E.
Expo Science Park
Expo Science Park is a science-themed park and exhibition complex in Daejeon, South Korea, originally developed for the 1993 Daejeon Expo and now serving as an educational and recreational landmark.
- 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_69c0086c2364819091e9fe2f58fa2517 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03a0240cc81909d7c75c7e6d630f7 |
completed | March 22, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1083361e08190aaba9e99a856e015 |
completed | March 23, 2026, 9:30 a.m. |
Created at: March 22, 2026, 4:03 p.m.