Triple
T28309194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .223 Remington |
E713949
|
entity |
| Predicate | typicalTwistRateRange |
P202456
|
FINISHED |
| Object | 1:7 to 1:12 inches |
—
|
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: 1:7 to 1:12 inches | Statement: [.223 Remington, typicalTwistRateRange, 1:7 to 1:12 inches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTwistRateRange Context triple: [.223 Remington, typicalTwistRateRange, 1:7 to 1:12 inches]
-
A.
twistType
Indicates the specific manner or category of twisting applied in a relationship or action between entities.
-
B.
twistCount
Indicates the number of twists or rotational turns applied or present in the relationship between the related entities.
-
C.
hasTwist
Indicates that an entity (such as a story, object, or feature) includes an unexpected change, reversal, or surprising element relative to what was previously established or anticipated.
-
D.
twistOffAngle
Indicates the angular amount or orientation by which something is twisted off from its original or reference position.
-
E.
typicalTrackLengthRange
Indicates the usual minimum and maximum lengths that a track associated with something tends to fall between.
- 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_69efb5256afc8190b9322d25c3ae6320 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_6a00818b20a881909fbf3bb33dcf7029 |
completed | May 10, 2026, 1 p.m. |
| PD | Predicate disambiguation | batch_6a0080f76f588190a933238861243d1a |
completed | May 10, 2026, 12:58 p.m. |
| PDg | Predicate description generation | batch_6a00818a671c819086d487dd5a5ba5d7 |
completed | May 10, 2026, 1 p.m. |
Created at: April 27, 2026, 11:39 p.m.