Triple
T5060657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messier 54 |
E114012
|
entity |
| Predicate | clusterConcentrationClass |
P40627
|
FINISHED |
| Object | III |
—
|
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: III | Statement: [Messier 54, clusterConcentrationClass, III]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clusterConcentrationClass Context triple: [Messier 54, clusterConcentrationClass, III]
-
A.
clusterDensity
Indicates the degree to which elements within a cluster are closely packed or concentrated relative to its size or volume.
-
B.
CMeans
Indicates that one concept or entity conveys, expresses, or serves as the means by which another concept or entity is understood or represented.
-
C.
ShapleySawyerConcentrationClass
chosen
Indicates the concentration class of a globular cluster as defined by the Shapley–Sawyer system, describing how centrally condensed or diffuse the cluster appears.
-
D.
concentrationClass
Indicates the classification of an entity based on the level or range of its concentration.
-
E.
classificationConsensus
Indicates that multiple agents or sources agree on the same classification or category assignment for a given entity or item.
- 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_69bd443c0c8c81908663b77afb28e165 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7472a1dc8190942f568a81fdd961 |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd715622b48190a3e8e49a5ef62b4a |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.