Triple
T12458921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HMS Illustrious |
E297735
|
entity |
| Predicate | armourFlightDeckThickness |
P18833
|
FINISHED |
| Object | 3 inches |
—
|
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: 3 inches | Statement: [HMS Illustrious, armourFlightDeckThickness, 3 inches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armourFlightDeckThickness Context triple: [HMS Illustrious, armourFlightDeckThickness, 3 inches]
-
A.
deckArmorThickness
chosen
Indicates the thickness of the armor plating on the horizontal deck surface of a vehicle, vessel, or structure.
-
B.
armourThickness
Indicates the measured thickness of an entity’s protective armor in the context of defense or shielding.
-
C.
frontHullArmorThickness
Indicates the thickness of the armor located on the front section of a vehicle’s hull.
-
D.
armoredBeltThickness
Indicates the thickness of an entity’s protective armored belt in the context of its defensive structure or design.
-
E.
flightDeckWidth
Indicates the measurement of how wide a vehicle’s flight deck is across its lateral (side-to-side) dimension.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.