Triple
T4787787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Sufi |
E106524
|
entity |
| Predicate | estimated |
P55909
|
FINISHED |
| Object | stellar brightness by naked-eye observations |
—
|
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: stellar brightness by naked-eye observations | Statement: [Al-Sufi, estimated, stellar brightness by naked-eye observations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimated Context triple: [Al-Sufi, estimated, stellar brightness by naked-eye observations]
-
A.
estimatedCost
Indicates the predicted or calculated monetary amount expected to be required for something, such as a project, item, or action.
-
B.
areEstimatedIn
chosen
Indicates that a value or quantity is approximated or inferred within a specified context, framework, or unit.
-
C.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
D.
estimatedCostComment
Indicates a textual note or explanation associated with an estimated cost, such as rationale, assumptions, or additional details about that estimate.
-
E.
separatesEstimationOf
Indicates that one entity distinguishes or isolates the estimation or assessment of another entity from other factors or components.
- 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_69bd43f4a9588190bf73e20bc27c03cc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65da229c81909c703393f7b9b71d |
completed | March 20, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69bd622e1b408190806c15c61519fc74 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:22 p.m.