Triple
T13426117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rally1 |
E313485
|
entity |
| Predicate | hasSafetyCellType |
P109860
|
FINISHED |
| Object | tubular spaceframe |
—
|
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: tubular spaceframe | Statement: [Rally1, hasSafetyCellType, tubular spaceframe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSafetyCellType Context triple: [Rally1, hasSafetyCellType, tubular spaceframe]
-
A.
hasSafetyCharacteristic
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
-
B.
hasSafetyRole
Indicates that an entity holds a responsibility or function related to safety within a given context or system.
-
C.
hasSecurityDimension
Indicates that something possesses or is associated with a particular aspect or dimension of security.
-
D.
hasSecurityClass
Indicates that an entity is assigned to or associated with a particular security classification level.
-
E.
hasSecurityPresence
Indicates that some form of security personnel, system, or measures are present at or associated with an entity or location.
- F. None of above. chosen
Provenance (4 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed066408190a416880affd8416e |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:40 p.m.