Triple
T13349894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1947 Kenneth Arnold sighting |
E318042
|
entity |
| Predicate | hasObjectShapeDescription |
P109135
|
FINISHED |
| Object | crescent-shaped |
—
|
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: crescent-shaped | Statement: [1947 Kenneth Arnold sighting, hasObjectShapeDescription, crescent-shaped]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasObjectShapeDescription Context triple: [1947 Kenneth Arnold sighting, hasObjectShapeDescription, crescent-shaped]
-
A.
hasObjectTypes
Indicates that something is associated with one or more specific categories or types of objects.
-
B.
hasShapeModel
Indicates that an entity is associated with a specific geometric or structural shape model that represents its form.
-
C.
hasObject
Indicates that an entity is associated with or possesses a particular object as part of a relationship or action.
-
D.
hasLowercaseShapeDescription
Indicates that the entity’s shape is described using a string consisting only of lowercase characters.
-
E.
hasComponentShape
Indicates that an entity includes, contains, or is characterized by a specific geometric or structural shape as one of its components.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8c2f1c819094f0970f35f18afa |
completed | April 11, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99073e4708190843bda3a1ae78f43 |
completed | April 11, 2026, 12:06 a.m. |
Created at: April 9, 2026, 9:31 p.m.