Triple
T27701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Defense Research Committee |
E552
|
entity |
| Predicate | hasNumberOfDivisions |
P1905
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [National Defense Research Committee, hasNumberOfDivisions, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfDivisions Context triple: [National Defense Research Committee, hasNumberOfDivisions, 5]
-
A.
hasDivisionLevel
Indicates that one entity is associated with a specific hierarchical or organizational division level of another entity.
-
B.
hasSubdivision
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
C.
divisionTitle
Indicates the formal name or title assigned to a specific division within a larger organization or structure.
-
D.
numberOfSpans
Indicates the total count of distinct spans or segments associated with an entity or within a specified context.
-
E.
hasNumberOfPlatforms
Indicates the relationship that specifies how many platforms are associated with a given 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a247798a348190bb943d38300ae3ef |
completed | Feb. 28, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69a24658749881909117b007ec3d8633 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a24778b73c81908e9f2eb8cdbcef73 |
completed | Feb. 28, 2026, 1:40 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.