Triple
T16353170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AS-90 turret |
E397107
|
entity |
| Predicate | designedToHouse |
P9494
|
FINISHED |
| Object | gun system |
—
|
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: gun system | Statement: [AS-90 turret, designedToHouse, gun system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedToHouse Context triple: [AS-90 turret, designedToHouse, gun system]
-
A.
houseProduced
Indicates that a house or housing unit was created, built, or generated by a particular agent, process, or source.
-
B.
intendedToHouse
Indicates that one entity is designed or meant to serve as a dwelling or accommodation space for another entity.
-
C.
houseUse
Indicates how a house or dwelling is used or purposed (e.g., residential, commercial, mixed-use).
-
D.
house2
Indicates a relationship where one entity is a secondary, related, or alternative house associated with another entity.
-
E.
isDesignedFor
chosen
Indicates that one entity has been created, planned, or optimized specifically to serve the needs, purposes, or use of 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2faccab748190b11e0808e422f2ea |
completed | April 18, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.