Triple
T2977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Las Campanas Observatory |
E55
|
entity |
| Predicate | primaryResearchField |
P3
|
FINISHED |
| Object | extragalactic astronomy |
—
|
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: extragalactic astronomy | Statement: [Las Campanas Observatory, primaryResearchField, extragalactic astronomy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryResearchField Context triple: [Las Campanas Observatory, primaryResearchField, extragalactic astronomy]
-
A.
fieldOfWork
chosen
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
B.
publicationType
Indicates the specific category or format of a published work that characterizes how it is issued or presented.
-
C.
academicAdvisor
Indicates that one entity serves as the academic advisor, providing formal guidance and oversight on academic matters, to another entity.
-
D.
primaryLanguageOfInstruction
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
E.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
- 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_69a2328f0e848190ac2840eaf2d5ebd2 |
completed | Feb. 28, 2026, 12:10 a.m. |
| NER | Named-entity recognition | batch_69a2346846608190b6b40d31f1dbd685 |
completed | Feb. 28, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69a233c396ec8190986608d07fb251d4 |
completed | Feb. 28, 2026, 12:16 a.m. |
Created at: Feb. 28, 2026, 12:13 a.m.