Triple
T16410893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauser HSc |
E398559
|
entity |
| Predicate | serialNumberRange |
P123323
|
FINISHED |
| Object | approximately 700000–970000 (wartime) |
—
|
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: approximately 700000–970000 (wartime) | Statement: [Mauser HSc, serialNumberRange, approximately 700000–970000 (wartime)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serialNumberRange Context triple: [Mauser HSc, serialNumberRange, approximately 700000–970000 (wartime)]
-
A.
articleNumberRange
Indicates that something is associated with or falls within a specified range of article numbers.
-
B.
hasShipNumberRange
Indicates that an entity is associated with ships whose identification numbers fall within a specified numeric range.
-
C.
serialNumber
Indicates a unique identifying code assigned to an individual item or instance within a series or batch.
-
D.
RVNumberRange
Indicates that a recreational vehicle’s number or identifier falls within a specified numeric range.
-
E.
includesNumberingRange
Indicates that one entity contains or covers a specified contiguous range of numbers associated with another 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328731a408190b38dcab0b7bb65ff |
completed | April 18, 2026, 6:45 a.m. |
| PD | Predicate disambiguation | batch_69e226fe1dd08190865c181721f8c348 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:09 a.m.