Triple
T20719403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grace Harper |
E509268
|
entity |
| Predicate | hasCyberneticComponent |
P41225
|
FINISHED |
| Object | subdermal armor |
—
|
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: subdermal armor | Statement: [Grace Harper, hasCyberneticComponent, subdermal armor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCyberneticComponent Context triple: [Grace Harper, hasCyberneticComponent, subdermal armor]
-
A.
hasCybernetic
chosen
Indicates that an entity possesses or is equipped with cybernetic enhancements, implants, or components.
-
B.
hasMechanicalAppendages
Indicates that an entity possesses one or more appendages that are mechanical or artificially constructed rather than purely biological.
-
C.
hasExoskeleton
Indicates that an entity possesses an external supportive or protective skeletal structure covering its body.
-
D.
hardwareComponent
Indicates that one entity is a physical hardware part or module that is contained in, attached to, or functionally part of another hardware system or device.
-
E.
featuresCyborg
Indicates that something includes or prominently presents a cyborg as part of its content or composition.
- 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_69e0b4c4cc648190b45fda6e2b20af56 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1d4de6c81908f8c98c2f1e70cc4 |
completed | April 21, 2026, 12:16 a.m. |
| PD | Predicate disambiguation | batch_69e5c04b31248190b9b9d91b5cb854e3 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:26 p.m.