Triple
T10574243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aliyah from Ethiopia |
E249568
|
entity |
| Predicate | estimatedNumberOfOlim |
P94708
|
FINISHED |
| Object | tens of thousands |
—
|
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: tens of thousands | Statement: [Aliyah from Ethiopia, estimatedNumberOfOlim, tens of thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfOlim Context triple: [Aliyah from Ethiopia, estimatedNumberOfOlim, tens of thousands]
-
A.
estimatedOarCount
Indicates the estimated number of oars associated with an entity, typically approximating how many oars it has or uses.
-
B.
expectedNumberOfAthletes
Indicates the anticipated or planned count of athletes expected to participate in a given context or event.
-
C.
capacityDuringOlympics
Indicates the seating or usage capacity of a venue, facility, or service specifically during the Olympic Games period.
-
D.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an entity.
-
E.
typicalNumberOfAthletes
Indicates the usual or average number of athletes associated with or participating in a given context, event, or entity.
- F. None of above. chosen
Provenance (4 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52749dda08190b0c9627a931c5848 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51901ff6c819095e7b528170a69dc |
completed | April 7, 2026, 2:47 p.m. |
| PDg | Predicate description generation | batch_69d5270eca0481908573b698390c5b08 |
completed | April 7, 2026, 3:47 p.m. |
Created at: April 6, 2026, 12:38 p.m.