Triple
T15386665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arc Whip |
E367933
|
entity |
| Predicate | userScale |
P118576
|
FINISHED |
| Object | Jaeger-scale weapon |
—
|
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: Jaeger-scale weapon | Statement: [Arc Whip, userScale, Jaeger-scale weapon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: userScale Context triple: [Arc Whip, userScale, Jaeger-scale weapon]
-
A.
areaScale
Indicates a proportional relationship where one area value is a scaled (enlarged or reduced) version of another by a specific factor.
-
B.
coversScale
Indicates that one entity spans, includes, or applies across the full range or extent of another entity’s scale.
-
C.
pixelScale
Indicates the ratio or conversion factor between pixel units and real-world or coordinate-space units in a representation or image.
-
D.
workScale
Indicates the relative magnitude, intensity, or scope at which a given work activity, project, or operation is carried out.
-
E.
associatedScale
Indicates that one entity is linked or connected to a particular scale used to measure, classify, or evaluate it.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e74ff70819094c1a85f51d6e228 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57005608190886cd01f640dfedb |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:19 a.m.