Triple
T4736478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messier 17 |
E105137
|
entity |
| Predicate | hasShapeAppearance |
P40118
|
FINISHED |
| Object | swan-like |
—
|
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: swan-like | Statement: [Messier 17, hasShapeAppearance, swan-like]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShapeAppearance Context triple: [Messier 17, hasShapeAppearance, swan-like]
-
A.
hasSilhouetteShape
chosen
Indicates that one entity has the overall outline or contour shape specified or characterized by another entity.
-
B.
hasApproximateShape
Indicates that one entity has a shape that is similar to, but not exactly the same as, the shape of another entity.
-
C.
hasWallShape
Indicates that an entity possesses a wall whose form or outline matches a specified geometric or structural shape.
-
D.
seeksToShape
Indicates an entity’s intention or effort to influence, mold, or determine the form, direction, or outcome of another entity or situation.
-
E.
hasTerminalShape
Indicates that one entity possesses or exhibits a particular terminal (end) shape defined by another 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64831c58819098758ac1f7839b3a |
completed | March 20, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69bd6221c3b881908604f35f8de6f16b |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:19 p.m.