Triple
T4994163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | W5 star-forming region |
E112202
|
entity |
| Predicate | hasEmission |
P46939
|
FINISHED |
| Object | strong hydrogen recombination lines |
—
|
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: strong hydrogen recombination lines | Statement: [W5 star-forming region, hasEmission, strong hydrogen recombination lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmission Context triple: [W5 star-forming region, hasEmission, strong hydrogen recombination lines]
-
A.
emissionType
chosen
Indicates the specific category or kind of emission associated with an entity or activity.
-
B.
emitted
Indicates that one entity has released, discharged, or sent out another entity, such as energy, particles, signals, or substances, into its surroundings.
-
C.
hasEmitter
Indicates that one entity functions as the source or origin that emits or sends out something associated with another entity.
-
D.
hasBurnUnit
Indicates that one entity (typically a medical facility) includes or is equipped with a specialized unit dedicated to the treatment and care of burn patients.
-
E.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
- 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_69bd4432b32c81909f3b3c6bd10f0653 |
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_69bd714aee2481908fb0dd5fa2daf3a1 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:34 p.m.