Triple
T16260602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ongwediva |
E394742
|
entity |
| Predicate | tradeFairFocus |
P67985
|
FINISHED |
| Object | business exhibitions |
—
|
LITERAL 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: business exhibitions | Statement: [Ongwediva, tradeFairFocus, business exhibitions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tradeFairFocus Context triple: [Ongwediva, tradeFairFocus, business exhibitions]
-
A.
tradeFocus
chosen
Indicates a primary emphasis on or specialization in a particular type of trade, transaction, or commercial activity within the relationship or context.
-
B.
hasTradeFairCenter
Indicates that a place or organization possesses or hosts a dedicated trade fair center where exhibitions or trade fairs are held.
-
C.
impactOnExhibitors
Indicates the effect or consequences that an event, decision, or condition has on exhibitors.
-
D.
industryEvent
Indicates that an event is related to a specific industry, such as a conference, trade show, or professional gathering focused on that industry.
-
E.
tradeNetwork
Indicates a relationship where entities are connected through the exchange of goods, services, or resources within an ongoing system of trade.
- F. None of above.
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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c3e5388190942b0237ab5d1f0f |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219f259e88190bf49d8408c04178e |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.