Triple
T19752499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sigma Sagittarii |
E474414
|
entity |
| Predicate | marksFeature |
P99152
|
FINISHED |
| Object | handle of the Teapot asterism |
—
|
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: handle of the Teapot asterism | Statement: [Sigma Sagittarii, marksFeature, handle of the Teapot asterism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marksFeature Context triple: [Sigma Sagittarii, marksFeature, handle of the Teapot asterism]
-
A.
markingFeature
chosen
Indicates a feature that serves as a distinguishing mark or identifier associated with an entity.
-
B.
marksOn
Indicates that one entity bears visible signs, traces, or imprints that have been made or left by another entity.
-
C.
marksLocationOf
Indicates that one entity serves as a marker, sign, or indicator specifying the location of another entity.
-
D.
markType
Indicates the specific category or kind of mark associated with or applied to an entity.
-
E.
marksBoundaryIn
Indicates that one entity serves as a boundary or delimiter within, or for a specific region or structure of, 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6529bcb8c8190bcca61a53be86757 |
completed | April 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69e5305016e08190b9561a96baecb0b8 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:48 p.m.