Triple
T14782014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LZ 130 Graf Zeppelin II |
E347412
|
entity |
| Predicate | gasCellsMaterial |
P116085
|
FINISHED |
| Object | goldbeater's skin |
—
|
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: goldbeater's skin | Statement: [LZ 130 Graf Zeppelin II, gasCellsMaterial, goldbeater's skin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gasCellsMaterial Context triple: [LZ 130 Graf Zeppelin II, gasCellsMaterial, goldbeater's skin]
-
A.
numberOfGasCells
Indicates the quantity of distinct gas cells associated with or contained within a given entity or system.
-
B.
engineBlockMaterial
Indicates the material from which an engine block is made or constructed.
-
C.
gasContent
Indicates that one entity has, contains, or is characterized by a certain amount or type of gas.
-
D.
fuelTankMaterial
Indicates the material from which a fuel tank is made.
-
E.
exampleMaterial
Indicates that something serves as a representative or illustrative material or sample of something else.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deca9de3f48190b7706925e2947cf5 |
completed | April 14, 2026, 11:15 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de90c5e3a08190868680b081308c1d |
completed | April 14, 2026, 7:08 p.m. |
Created at: April 10, 2026, 1:31 a.m.