Triple
T6762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Civilian Conservation Corps |
E134
|
entity |
| Predicate | numberOfParticipants |
P1131
|
FINISHED |
| Object | over 3,000,000 |
—
|
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: over 3,000,000 | Statement: [Civilian Conservation Corps, numberOfParticipants, over 3,000,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfParticipants Context triple: [Civilian Conservation Corps, numberOfParticipants, over 3,000,000]
-
A.
hasNumberOfStudentAthletes
Indicates the relationship that specifies how many student athletes are associated with a given entity.
-
B.
collectionSize
Indicates the total number of items contained within a specified collection.
-
C.
numberOfChildren
Indicates the total count of children that an entity has.
-
D.
visitorCount
Indicates the number of visitors associated with a particular entity, context, or time period.
-
E.
participatedInEvent
Indicates that an entity took part in or was actively involved in a specific event.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2421836f08190b54fc40edeb1a96b |
completed | Feb. 28, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69a23fe064c881909496fd0e6b0e18d7 |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a242174cd4819095f78b221e1b41f1 |
completed | Feb. 28, 2026, 1:17 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.