Triple
T7116755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Bertha howitzer |
E165838
|
entity |
| Predicate | approximateWeightCategory |
P26162
|
FINISHED |
| Object | hundreds of tons including transport equipment |
—
|
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: hundreds of tons including transport equipment | Statement: [Big Bertha howitzer, approximateWeightCategory, hundreds of tons including transport equipment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateWeightCategory Context triple: [Big Bertha howitzer, approximateWeightCategory, hundreds of tons including transport equipment]
-
A.
approximateWeightInPounds
Indicates the estimated weight of an entity expressed in pounds, rather than an exact measured value.
-
B.
approximateMass
Indicates that one entity has a mass value that is an estimate or close approximation of the mass of another entity.
-
C.
averageWeight
Indicates the typical or mean weight value associated with an entity or group of entities.
-
D.
weightRangeDescription
chosen
Indicates the textual description that specifies the range within which an entity’s weight falls.
-
E.
sizeCategory
Indicates the relative size classification assigned to an entity compared to others (e.g., small, medium, large).
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e617a528819085d4b8e1b5699966 |
completed | March 27, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c4f9788190830288d00cc37026 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:43 p.m.