Triple
T9277852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewis gun |
E222994
|
entity |
| Predicate | standardPanCapacity |
P80385
|
FINISHED |
| Object | 47 rounds |
—
|
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: 47 rounds | Statement: [Lewis gun, standardPanCapacity, 47 rounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardPanCapacity Context triple: [Lewis gun, standardPanCapacity, 47 rounds]
-
A.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
B.
unitCapacity
chosen
Indicates the maximum quantity or load that a single unit is designed or allowed to hold, process, or accommodate.
-
C.
storageCapacity
Indicates the maximum amount of data or material that a storage entity can hold.
-
D.
capacityPerSide
Indicates the maximum quantity or volume that each individual side or unit in a pair can hold or accommodate.
-
E.
capacityCategory
Indicates the classification of something based on the amount or volume it can hold, handle, or accommodate.
- 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_69ca842123588190b3f2e1a69037d141 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd07cb28e081909b2754756c8f5dd0 |
completed | April 1, 2026, 11:55 a.m. |
| PD | Predicate disambiguation | batch_69cc7a576ec88190bbb787eb82e2e539 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:34 p.m.