Triple
T14263448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Marching Twenty-Four |
E353580
|
entity |
| Predicate | hasUnitSize |
P3664
|
FINISHED |
| Object | platoon-sized unit |
—
|
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: platoon-sized unit | Statement: [The Marching Twenty-Four, hasUnitSize, platoon-sized unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnitSize Context triple: [The Marching Twenty-Four, hasUnitSize, platoon-sized unit]
-
A.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
B.
typicalUnitSize
chosen
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
C.
hasUnitStructure
Indicates that an entity possesses a specific internal organization or arrangement that defines its structural composition.
-
D.
minimumUnitSize
Indicates that there is a smallest allowable or defined size or quantity for the unit involved in the relationship.
-
E.
hasSize
Indicates that one entity possesses a particular physical magnitude or extent, such as length, volume, or overall dimensions.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de63563fc88190b0abdbf8529c65eb |
completed | April 14, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69de2a7d586c8190846ff242bbf5ac53 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:09 a.m.