Triple
T8131047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L86 Light Support Weapon |
E189851
|
entity |
| Predicate | hasReceiverMaterial |
P1845
|
FINISHED |
| Object | stamped steel |
—
|
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: stamped steel | Statement: [L86 Light Support Weapon, hasReceiverMaterial, stamped steel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReceiverMaterial Context triple: [L86 Light Support Weapon, hasReceiverMaterial, stamped steel]
-
A.
hasMaterialType
chosen
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
B.
hasReconstructionMaterial
Indicates that something is associated with, composed of, or utilizes a particular material for its reconstruction.
-
C.
hasMaterialOption
Indicates that an entity can be made from, or is available in, one or more alternative materials.
-
D.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
E.
supportsMaterial
Indicates that one entity provides structural or functional support to a material entity, enabling it to be held, stabilized, or borne.
- 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_69ca82bcb4848190a9a9d036ad768642 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4c4c2e388190b86854f8b1765e61 |
completed | March 31, 2026, 4:23 a.m. |
| PD | Predicate disambiguation | batch_69cb3696379c8190a20965e59ed8f370 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:34 p.m.