Triple
T2410260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marsyas |
E50371
|
entity |
| Predicate | supportStructure |
P18077
|
FINISHED |
| Object | steel armatures |
—
|
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: steel armatures | Statement: [Marsyas, supportStructure, steel armatures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportStructure Context triple: [Marsyas, supportStructure, steel armatures]
-
A.
supportsStructure
chosen
Indicates that one entity bears or provides physical support to another entity, helping to hold it up or maintain its structural stability.
-
B.
supportBase
Indicates that one entity serves as a foundational or backing structure that physically or functionally supports another entity.
-
C.
support
Indicates that one entity provides assistance, endorsement, or backing to another entity or its actions.
-
D.
supportsInfrastructure
Indicates that one entity provides resources, services, or capabilities that enable the operation, maintenance, or development of another entity’s infrastructure.
-
E.
usedStructure
Indicates that one entity makes use of, relies on, or operates through a particular structure (physical, logical, or organizational) to perform its function or action.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abceab9ce881909ae0a2f34515c11e |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5a530e8819094105aa92dfaf6b3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:58 p.m.