Triple
T18771608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NGC 2023 |
E459027
|
entity |
| Predicate | hasDustTemperature |
P4459
|
FINISHED |
| Object | ~50–80 K |
—
|
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: ~50–80 K | Statement: [NGC 2023, hasDustTemperature, ~50–80 K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDustTemperature Context triple: [NGC 2023, hasDustTemperature, ~50–80 K]
-
A.
hasDust
Indicates that one entity possesses, contains, or is covered with dust.
-
B.
hasTemperature
chosen
Indicates that an entity possesses or is characterized by a specific temperature value.
-
C.
hasEffectiveTemperature
Indicates that an entity (typically a star or other astronomical object) possesses a specific effective surface temperature characterizing its emitted radiation.
-
D.
operatingTemperature
Indicates the range or specific value of temperature within which an entity is designed or allowed to function properly.
-
E.
hasTemperatureCategory
Indicates that an entity is associated with a specific qualitative temperature classification (e.g., hot, cold, warm).
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e59335a01881908731371be1e27a6b |
completed | April 20, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69e48d0b7b708190877951b6e6cdcbc4 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:52 a.m.