Triple
T20895910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WR-40 Langusta |
E514533
|
entity |
| Predicate | hasArmoredCab |
P132245
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [WR-40 Langusta, hasArmoredCab, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArmoredCab Context triple: [WR-40 Langusta, hasArmoredCab, yes]
-
A.
usesArmoredVehicle
Indicates that an entity employs or operates an armored vehicle in performing an action or fulfilling a role.
-
B.
hasArmorPlating
chosen
Indicates that one entity is equipped with or covered by protective armor plating in relation to another entity or context.
-
C.
hasArm
Indicates that one entity possesses or is equipped with an arm as a physical part or component of itself.
-
D.
hasArrestingGear
Indicates that an entity is equipped with a system or mechanism used to rapidly decelerate and stop another entity, typically during landing or capture.
-
E.
hasCabType
Indicates that an entity is associated with or characterized by a specific type or category of cab.
- 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_69e0b4f7ebe48190952a85547a0f31a1 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6d06233588190942493b709e30820 |
completed | April 21, 2026, 1:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c9ac91108190a6700fcdf2f11890 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:47 p.m.