Triple
T27759428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Very Large Array |
E701424
|
entity |
| Predicate | railTrackLengthPerArm |
P163223
|
FINISHED |
| Object | about 21 km |
—
|
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: about 21 km | Statement: [Very Large Array, railTrackLengthPerArm, about 21 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railTrackLengthPerArm Context triple: [Very Large Array, railTrackLengthPerArm, about 21 km]
-
A.
railTracks
Indicates that one entity consists of, includes, or is associated with rail tracks used for guiding trains or rail vehicles.
-
B.
rollingStockLength
Indicates the length measurement of a piece of rolling stock in a rail or transit system.
-
C.
numberOfRailwayTracks
Indicates the quantity of railway tracks associated with or present at a given entity or location.
-
D.
trainsPerSide
Indicates the number of trains allocated or operating on each side (e.g., direction, platform, or segment) within a system or configuration.
-
E.
railwayLineLength
Indicates the total measured length of a railway line.
- 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_69ef6a5193808190816eb7d0020b2d87 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f637645f088190bd7c695784a5f429 |
completed | May 2, 2026, 5:41 p.m. |
| PD | Predicate disambiguation | batch_69f63188e7408190af8ce8b93d128c63 |
completed | May 2, 2026, 5:16 p.m. |
| PDg | Predicate description generation | batch_69f6352df6148190bc10772cd40bd7b3 |
completed | May 2, 2026, 5:32 p.m. |
Created at: April 27, 2026, 4:25 p.m.