Triple
T8131048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L86 Light Support Weapon |
E189851
|
entity |
| Predicate | hasFurnitureMaterial |
P1272
|
FINISHED |
| Object | polymer |
—
|
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: polymer | Statement: [L86 Light Support Weapon, hasFurnitureMaterial, polymer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFurnitureMaterial Context triple: [L86 Light Support Weapon, hasFurnitureMaterial, polymer]
-
A.
hasDoorMaterial
Indicates that an entity’s door is made of, or primarily composed of, a specified material.
-
B.
materialUsed
chosen
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
containsFurnitureBy
Indicates that one entity includes or holds furniture items that are provided, created, or specified by another entity.
-
D.
hasFloorMaterial
Indicates that an entity’s floor is made of, covered with, or constructed from a specified material.
-
E.
hasLiningMaterial
Indicates that one entity uses or contains another entity as the material forming its inner lining.
- 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.