Triple
T3274201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fendouzhe |
E68719
|
entity |
| Predicate | hasLifeSupport |
P21784
|
FINISHED |
| Object | closed life-support system |
—
|
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: closed life-support system | Statement: [Fendouzhe, hasLifeSupport, closed life-support system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLifeSupport Context triple: [Fendouzhe, hasLifeSupport, closed life-support system]
-
A.
supportsLife
Indicates that one entity provides conditions or resources that allow another entity to live, grow, or remain biologically viable.
-
B.
hasOnboardSystems
chosen
Indicates that an entity is equipped with or contains specific onboard systems or subsystems.
-
C.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
-
D.
hasLifeboatService
Indicates that a lifeboat service is available or provided in relation to the subject entity.
-
E.
hasLift
Indicates that one entity is equipped with, contains, or provides access to a lift (elevator).
- 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adaff8a440819092509bc8511b2785 |
completed | March 8, 2026, 5:20 p.m. |
| PD | Predicate disambiguation | batch_69ada420167c81909b6e2702db296d9e |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:10 p.m.