Triple
T5452960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M13/40 medium tank |
E122410
|
entity |
| Predicate | armorFrontMaximum |
P45211
|
FINISHED |
| Object | approximately 30 mm |
—
|
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 30 mm | Statement: [M13/40 medium tank, armorFrontMaximum, approximately 30 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armorFrontMaximum Context triple: [M13/40 medium tank, armorFrontMaximum, approximately 30 mm]
-
A.
armorThicknessMax
chosen
Indicates the maximum thickness of armor that an entity possesses or can withstand.
-
B.
frontArmorRange
Indicates the range or extent of protective armor coverage on the front-facing side of an entity.
-
C.
armorFeature
Indicates that one entity is a functional or descriptive feature of another entity’s armor.
-
D.
frontHullArmorThickness
Indicates the thickness of the armor located on the front section of a vehicle’s hull.
-
E.
armourThickness
Indicates the measured thickness of an entity’s protective armor in the context of defense or shielding.
- 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:08 p.m.