Triple
T650372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Brigades |
E11332
|
entity |
| Predicate | estimatedNumberOfParticipants |
P1131
|
FINISHED |
| Object | 30000 |
—
|
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: 30000 | Statement: [International Brigades, estimatedNumberOfParticipants, 30000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfParticipants Context triple: [International Brigades, estimatedNumberOfParticipants, 30000]
-
A.
numberOfParticipants
chosen
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
B.
approximateAudienceSize
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
C.
hasParticipants
Indicates that an event, activity, or situation involves one or more entities as participants in it.
-
D.
hasApproximateTotalSpeakers
Indicates that an entity is associated with an estimated or roughly calculated number of total speakers, rather than an exact count.
-
E.
numberOfPersons
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f33b6d881908b6662b73d6fe833 |
completed | March 1, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69a49d0eade081909c47e85ed55f808d |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.