Triple
T14030460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucas sequences |
E337572
|
entity |
| Predicate | firstKindInitialConditions |
P46246
|
FINISHED |
| Object | U_0 = 0, U_1 = 1 |
—
|
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: U_0 = 0, U_1 = 1 | Statement: [Lucas sequences, firstKindInitialConditions, U_0 = 0, U_1 = 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstKindInitialConditions Context triple: [Lucas sequences, firstKindInitialConditions, U_0 = 0, U_1 = 1]
-
A.
firstOrdinary
Indicates that the subject is the first entity to hold or occupy an ordinary (non-special, standard) position, role, or status in a given sequence or context.
-
B.
firstTerms
chosen
Indicates that the related entities are the initial elements or starting terms in a sequence, series, or ordered collection.
-
C.
firstStageType
Indicates that one entity is the type or category of the first stage or initial phase associated with another entity.
-
D.
firstCongruence
Indicates that one entity is the initial or primary instance in a set of congruent (equivalent in form or measure) entities or relationships.
-
E.
initialStatus
Indicates the original or starting state assigned to an entity before any changes or updates occur.
- 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.