Triple
T2783501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thirty Meter Telescope |
E61751
|
entity |
| Predicate | scientificAimsInclude |
P7242
|
FINISHED |
| Object | direct imaging of exoplanets |
—
|
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: direct imaging of exoplanets | Statement: [Thirty Meter Telescope, scientificAimsInclude, direct imaging of exoplanets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scientificAimsInclude Context triple: [Thirty Meter Telescope, scientificAimsInclude, direct imaging of exoplanets]
-
A.
scienceGoals
chosen
Indicates the objectives or intended outcomes that guide and justify a scientific activity, project, or investigation.
-
B.
isScientific
Indicates that something pertains to or is based on systematic scientific methods, principles, or knowledge.
-
C.
scientificInstruments
Indicates that one entity is a scientific instrument used by, associated with, or relevant to another entity in the context of scientific measurement or research.
-
D.
definesAimsOf
Indicates that one entity specifies or establishes the goals, purposes, or intended outcomes of another entity.
-
E.
researchTopic
Indicates that a subject conducts or focuses research on a particular topic or area of study.
- 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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdd00b65c8190a8ea444308c4fa2b |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.