Triple
T4167623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyle gun |
E84481
|
entity |
| Predicate | hasProjectileType |
P1454
|
FINISHED |
| Object | cylindrical projectile |
—
|
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: cylindrical projectile | Statement: [Lyle gun, hasProjectileType, cylindrical projectile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProjectileType Context triple: [Lyle gun, hasProjectileType, cylindrical projectile]
-
A.
hasWeaponType
Indicates that an entity is associated with or equipped with a specific type or category of weapon.
-
B.
involvesProjectile
chosen
Indicates that the action or event includes the use, presence, or motion of a projectile as a key component of the interaction between entities.
-
C.
hasProjectType
Indicates that an entity is associated with, or classified under, a specific type or category of project.
-
D.
hasParticleType
Indicates that an entity is associated with, composed of, or characterized by a specific type or category of particle.
-
E.
prohibitedWeaponType
Indicates that a particular type of weapon is classified as not allowed or forbidden under specified rules, laws, or agreements.
- 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02c43a7481909eed7cb8c14deb0c |
completed | March 9, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69af018fb0948190a9701b2e8e5d9bac |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:44 p.m.