Triple
T36958209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arachnotron |
E914240
|
entity |
| Predicate | hasCyberneticEnhancements |
P41225
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Arachnotron, hasCyberneticEnhancements, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCyberneticEnhancements Context triple: [Arachnotron, hasCyberneticEnhancements, yes]
-
A.
hasCybernetic
chosen
Indicates that an entity possesses or is equipped with cybernetic enhancements, implants, or components.
-
B.
isCyborg
Indicates that an entity is a being composed of both biological and artificial (mechanical or electronic) components.
-
C.
hasExoskeleton
Indicates that an entity possesses an external supportive or protective skeletal structure covering its body.
-
D.
hasMechanicalAppendages
Indicates that an entity possesses one or more appendages that are mechanical or artificially constructed rather than purely biological.
-
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_69f76e8c498c8190b2842db80aea8b3b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:13 p.m.