Triple
T13246412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAM 28000 |
E315416
|
entity |
| Predicate | hasHardenedElectronics |
P88194
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [SAM 28000, hasHardenedElectronics, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHardenedElectronics Context triple: [SAM 28000, hasHardenedElectronics, true]
-
A.
hasHardware
Indicates that one entity possesses, includes, or is equipped with specific hardware components or devices.
-
B.
hasElectronicsFeature
chosen
Indicates that an entity possesses or is characterized by a specific electronic-related feature or capability.
-
C.
hasHardenedShelters
Indicates that an entity possesses or is equipped with shelters that are reinforced or hardened for protection.
-
D.
hardwareUsed
Indicates that a particular piece of hardware is utilized or employed in performing an action, process, or function involving another entity.
-
E.
hasRugged
Indicates that something possesses a rough, uneven, or tough physical character or surface.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d5c09f88190bb1566a6d8c073a6 |
completed | April 10, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69d98bcca7d88190a3e68e99ed3a29e6 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:23 p.m.