Triple
T147147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magellan Echellette Spectrograph |
E3354
|
entity |
| Predicate | dataProduct |
P3585
|
FINISHED |
| Object | two-dimensional echelle spectra |
—
|
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: two-dimensional echelle spectra | Statement: [Magellan Echellette Spectrograph, dataProduct, two-dimensional echelle spectra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataProduct Context triple: [Magellan Echellette Spectrograph, dataProduct, two-dimensional echelle spectra]
-
A.
hasProduct
chosen
Indicates that an entity possesses, offers, or is associated with a particular product.
-
B.
produces
Indicates that one entity creates, generates, or yields another entity as a result or output.
-
C.
mediaMarket
Indicates a relationship where a media outlet or content provider serves, targets, or operates within a particular geographic or demographic market.
-
D.
notableProduct
Indicates that a product is especially significant, prominent, or well-known in relation to the associated entity.
-
E.
designedIn
Indicates that something was created, planned, or conceived during a particular time period or at a specific location.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256580c2c8190beecca60ca8595f3 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.