Triple
T3214164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fibonacci sequence |
E67350
|
entity |
| Predicate | hasInitialConditions |
P29157
|
FINISHED |
| Object | F(0) = 0 |
—
|
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: F(0) = 0 | Statement: [Fibonacci sequence, hasInitialConditions, F(0) = 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInitialConditions Context triple: [Fibonacci sequence, hasInitialConditions, F(0) = 0]
-
A.
hasInitial
Indicates that one entity possesses or is associated with the first letter or starting character of another entity’s name or value.
-
B.
hasCondition
Indicates that an entity possesses, experiences, or is affected by a particular condition or state.
-
C.
hasNumberOfInitialNodes
Indicates the relationship that specifies how many initial or starting nodes are associated with a given entity or structure.
-
D.
hasFirstTerm
chosen
Indicates that an entity is associated with a specific first term in an ordered sequence, period, or series.
-
E.
hasInitialLetters
Indicates that one entity’s initial letters or acronym are derived from or correspond to the other 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaabd01d48190be0dc610b9987a25 |
completed | March 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69ad9e09b83881908801d79c3d9254f9 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.