Triple
T23367327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NGC 1073 |
E593359
|
entity |
| Predicate | spiralArmTightness |
P152446
|
FINISHED |
| Object | loosely wound |
—
|
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: loosely wound | Statement: [NGC 1073, spiralArmTightness, loosely wound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spiralArmTightness Context triple: [NGC 1073, spiralArmTightness, loosely wound]
-
A.
hasSpiralArmCount
Indicates the number of spiral arms that a spiral-structured entity possesses.
-
B.
isMajorSpiralArmOf
Indicates that one spiral arm is a primary, large-scale arm structure belonging to or forming a main component of a spiral galaxy.
-
C.
hasSpiralArms
Indicates that the subject possesses spiral-shaped arm-like structures extending outward, typically arranged in a winding or coiled pattern.
-
D.
hasNoProminentSpiralArms
Indicates that the object lacks clearly defined or visually dominant spiral arm structures.
-
E.
isNearestLargeSpiralTo
Indicates that one entity is the closest large spiral (e.g., in distance or proximity) to another entity among all comparable candidates.
- F. None of above. chosen
Provenance (4 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0ad621881908a909f236e6e9c90 |
completed | April 29, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69f061c7aaa48190a58ce93f87155ffc |
completed | April 28, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 5:32 p.m.