Triple
T38156926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mobile World Congress 2015 |
E952910
|
entity |
| Predicate | attendeesApprox |
P3653
|
FINISHED |
| Object | 90000 |
—
|
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: 90000 | Statement: [Mobile World Congress 2015, attendeesApprox, 90000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attendeesApprox Context triple: [Mobile World Congress 2015, attendeesApprox, 90000]
-
A.
guestCountApproximate
Indicates that the number of guests involved is represented as an estimated or approximate count rather than an exact figure.
-
B.
hasApproximateNumberOfPeople
Indicates that an entity is associated with an estimated or approximate count of people, rather than an exact number.
-
C.
audienceSizeApproximate
chosen
Indicates an estimated or approximate number of people in the audience for an event or content.
-
D.
approximateAudienceSize
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
E.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
- 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_69f76f0a67f4819080c492f61d688fcc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:21 p.m.