Triple
T2797591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Expo '75 |
E53075
|
entity |
| Predicate | category |
P87
|
FINISHED |
| Object | Specialized Expo |
E271986
|
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: Specialized Expo | Statement: [Expo '75, category, Specialized Expo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Specialized Expo Context triple: [Expo '75, category, Specialized Expo]
-
A.
Specialised Expos
chosen
Specialised Expos are internationally sanctioned, theme-focused world exhibitions that are smaller and shorter in duration than Universal Expos and must adhere to rules set by the Bureau International des Expositions.
-
B.
Expo
Expo is a popular brand best known for its dry-erase markers and related whiteboard accessories commonly used in schools, offices, and homes.
-
C.
The Expo
The Expo is a well-known multipurpose event and exhibition venue in Portland, Oregon, hosting trade shows, conventions, and community events.
-
D.
IDG World Expo
IDG World Expo is a trade show and conference organizer known for producing major technology events and exhibitions worldwide.
-
E.
Hannover Messe
Hannover Messe is one of the world’s largest and most influential industrial technology trade fairs, held annually in Hanover, Germany.
- 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_69ab495a90788190941b6917e1eca3a6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abddf204148190a53f3f30d645d94c |
completed | March 7, 2026, 8:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc66798148190bd7b163043167409 |
completed | March 10, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:58 p.m.