Triple
T9332752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Klem |
E224562
|
entity |
| Predicate | usedProtectiveEquipment |
P2728
|
FINISHED |
| Object | inside chest protector |
—
|
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: inside chest protector | Statement: [Bill Klem, usedProtectiveEquipment, inside chest protector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedProtectiveEquipment Context triple: [Bill Klem, usedProtectiveEquipment, inside chest protector]
-
A.
protectiveEquipment
Indicates that one entity serves as protective equipment used to safeguard another entity from harm or risk.
-
B.
safetyEquipment
Indicates that one entity serves as safety equipment used to protect another entity from harm or danger.
-
C.
usesEquipment
chosen
Indicates that an entity employs or operates a particular piece of equipment to perform an action or fulfill a function.
-
D.
providesProtectionIn
Indicates that one entity offers protection or safeguarding to another entity within a specified context, location, or situation.
-
E.
usedInWork
Indicates that something (such as a concept, method, material, or component) is employed or applied within a particular work, project, or creation.
- 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_69ca8427a0c08190b749831d5ea98f02 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd37afceb88190ad7ffbc7b47a1caa |
completed | April 1, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cc7a643924819097f01144734901cf |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:39 p.m.