Triple
T2582148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairchild C-119 Flying Boxcar |
E57115
|
entity |
| Predicate | troopCapacity |
P17501
|
FINISHED |
| Object | about 62 troops |
—
|
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: about 62 troops | Statement: [Fairchild C-119 Flying Boxcar, troopCapacity, about 62 troops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: troopCapacity Context triple: [Fairchild C-119 Flying Boxcar, troopCapacity, about 62 troops]
-
A.
paratroopCapacity
chosen
Indicates the maximum number of paratroopers or amount of airborne troops that something (typically a vehicle or vessel) is capable of carrying or deploying.
-
B.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
-
C.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
D.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
E.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3c843bc8190837cea3441bf3ca1 |
completed | March 7, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69abd0cfeae08190aed03866ba071c5c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.