Triple
T201334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ames Research Center 80-by-120-Foot Wind Tunnel |
E4510
|
entity |
| Predicate | testSectionSize |
P7759
|
FINISHED |
| Object | 80 by 120 feet |
—
|
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: 80 by 120 feet | Statement: [Ames Research Center 80-by-120-Foot Wind Tunnel, testSectionSize, 80 by 120 feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: testSectionSize Context triple: [Ames Research Center 80-by-120-Foot Wind Tunnel, testSectionSize, 80 by 120 feet]
-
A.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
-
B.
fieldSize
chosen
Indicates the magnitude or dimensions of a field associated with an entity or context.
-
C.
approximateSize
Indicates that one entity has a size that is roughly or approximately equal to the size of another entity.
-
D.
bodySize
Indicates the relative physical magnitude or scale of an entity’s body, such as how large or small it is.
-
E.
packetSize
Indicates the size or amount of data contained in a packet within a communication or data transfer context.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c2ead8481909996042efcae5e9d |
completed | Feb. 28, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69a25b4a0d448190a6fa6aeb30dc7e13 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:51 a.m.