Triple
T14030408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | golden ratio |
E337571
|
entity |
| Predicate | hasApproximateFraction |
P9773
|
FINISHED |
| Object | 8/5 |
—
|
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: 8/5 | Statement: [golden ratio, hasApproximateFraction, 8/5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateFraction Context triple: [golden ratio, hasApproximateFraction, 8/5]
-
A.
hasFraction
Indicates that one entity represents a fractional part or proportion of another entity.
-
B.
hasApproximateValue
chosen
Indicates that one entity’s value is close to, but not exactly equal to, the value of another entity within an acceptable margin of error.
-
C.
hasApproximateRate
Indicates that one entity is associated with another entity representing an estimated or non-exact rate or frequency.
-
D.
containsApproximately
Indicates that one entity holds or includes another entity in a quantity or proportion that is close to, but not exactly, a specified amount.
-
E.
hasApproximateUse
Indicates that one entity is used for a purpose that is similar to, but not exactly the same as, the use or function 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa9f8248190930954d609dee5f1 |
completed | April 14, 2026, 12:14 p.m. |
| PD | Predicate disambiguation | batch_69de05ab36b48190920efb1869bdb1fe |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.