Triple
T19901814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | W5 H II region |
E478308
|
entity |
| Predicate | hasNebularComponent |
P135119
|
FINISHED |
| Object | ionized gas |
—
|
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: ionized gas | Statement: [W5 H II region, hasNebularComponent, ionized gas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNebularComponent Context triple: [W5 H II region, hasNebularComponent, ionized gas]
-
A.
hasHostNebula
Indicates that one astronomical object, typically a star or stellar remnant, is associated with or embedded within a particular nebula that serves as its surrounding host.
-
B.
hasLayComponent
Indicates that an entity includes or is associated with a specific lay (non-professional or non-expert) component as part of its structure or composition.
-
C.
hasComponentModel
Indicates that an entity includes or is associated with a specific component model as part of its structure or configuration.
-
D.
hasNebulosity
chosen
Indicates that one entity possesses or exhibits nebulous, cloud-like, or diffuse characteristics associated with nebulosity.
-
E.
hasSubcomponent
Indicates that one entity is a constituent part or component of another, larger entity.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65941977081909e2f94724eb2c3c0 |
completed | April 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:52 p.m.