Triple
T20810524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NGC 1850 |
E512284
|
entity |
| Predicate | hasUnusualProperty |
P133426
|
FINISHED |
| Object | double-cluster-like structure |
—
|
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: double-cluster-like structure | Statement: [NGC 1850, hasUnusualProperty, double-cluster-like structure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnusualProperty Context triple: [NGC 1850, hasUnusualProperty, double-cluster-like structure]
-
A.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
B.
hasUnusualMorphology
chosen
Indicates that an entity possesses structural or anatomical features that deviate significantly from what is typical or expected for its kind.
-
C.
hasFictionalProperty
Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary context.
-
D.
hasSpecialRules
Indicates that certain entities are governed by additional or exceptional rules that differ from the standard ones.
-
E.
hasHighPropertyValues
Indicates that the associated entity possesses property values that are above a defined or typical threshold.
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2d27a4881908b34679385d8b94b |
completed | April 21, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69e5c99ca55481908e8d434fa901cfd6 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:40 p.m.