Triple
T5720041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Challenger 1 |
E126119
|
entity |
| Predicate | hullLayout |
P66069
|
FINISHED |
| Object | driver front, fighting compartment centre, engine rear |
—
|
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: driver front, fighting compartment centre, engine rear | Statement: [Challenger 1, hullLayout, driver front, fighting compartment centre, engine rear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hullLayout Context triple: [Challenger 1, hullLayout, driver front, fighting compartment centre, engine rear]
-
A.
hullConstruction
Indicates the process or activity of building, assembling, or forming the main body (hull) of a vessel or similar structure.
-
B.
usedHullNumberSystem
Indicates that an entity employed a hull numbering system to identify or classify ships or vessels.
-
C.
hullColor
Indicates the color attribute assigned to the outer surface (hull) of an object, typically a vehicle or vessel.
-
D.
hullNumber
Indicates the unique identifying number assigned to the hull of a ship or vessel.
-
E.
hullType
Indicates the specific structural design or configuration of an object's hull, typically classifying how its outer body or shell is shaped or constructed.
- 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_69c0082e3d548190950169847b43043b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c47f4c81909e6849c3be3e951c |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c028fec2bc819083f5dca6a8d9d435 |
completed | March 22, 2026, 5:38 p.m. |
Created at: March 22, 2026, 3:46 p.m.