Triple
T22149227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saracen armoured personnel carrier |
E547368
|
entity |
| Predicate | armourDescription |
P11885
|
FINISHED |
| Object | light armour |
—
|
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: light armour | Statement: [Saracen armoured personnel carrier, armourDescription, light armour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armourDescription Context triple: [Saracen armoured personnel carrier, armourDescription, light armour]
-
A.
armour
Indicates that an entity provides protective covering or defense for another entity.
-
B.
armorType
chosen
Indicates the specific category or classification of protective armor associated with an entity.
-
C.
armourCoverage
Indicates the extent or area of a subject’s body or structure that is protected or covered by armour.
-
D.
armourThickness
Indicates the measured thickness of an entity’s protective armor in the context of defense or shielding.
-
E.
armourProtection
Indicates that one entity provides protective armor or defensive covering for another entity.
- 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_69e11e3b52088190ad5df386d01eb2fb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129f2c0e881909c3488bb5eb5959d |
completed | April 28, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69e71b384e008190b723c9a0f1089d66 |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:33 p.m.