Triple
T13196508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A5 rocket |
E314123
|
entity |
| Predicate | materialContributionTo |
P108995
|
FINISHED |
| Object | aerodynamic layout of V-2 |
—
|
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: aerodynamic layout of V-2 | Statement: [A5 rocket, materialContributionTo, aerodynamic layout of V-2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialContributionTo Context triple: [A5 rocket, materialContributionTo, aerodynamic layout of V-2]
-
A.
materialConcept
Indicates that one entity represents or refers to a material-related concept associated with another entity.
-
B.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
materialProvidedFor
Indicates that one entity supplies or makes available a material for use, processing, or incorporation by another entity or purpose.
-
D.
material
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
-
E.
materialDepicted
Indicates that a work or representation visually portrays or includes a particular material as part of its subject.
- 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc6bc108190b5a6a265bf6e9fd4 |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98ceeb22c8190a6be666031d9e5a4 |
completed | April 10, 2026, 11:51 p.m. |
Created at: April 9, 2026, 9:16 p.m.