Triple
T7581751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gauss–Matuyama geomagnetic reversal |
E179503
|
entity |
| Predicate | hasTimescaleDesignation |
P64790
|
FINISHED |
| Object | C2An–C2r boundary |
—
|
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: C2An–C2r boundary | Statement: [Gauss–Matuyama geomagnetic reversal, hasTimescaleDesignation, C2An–C2r boundary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTimescaleDesignation Context triple: [Gauss–Matuyama geomagnetic reversal, hasTimescaleDesignation, C2An–C2r boundary]
-
A.
supportsTimescale
Indicates that one entity is capable of operating with, accommodating, or being compatible with a specified timescale or range of temporal resolutions.
-
B.
timescale
Indicates the temporal scale or duration over which a process, relationship, or effect occurs or is evaluated.
-
C.
hasTimeDimension
Indicates that something possesses or is associated with a temporal aspect, such as duration, point in time, or time-based variation.
-
D.
hasScales
Indicates that an entity possesses scales as a surface covering or body feature.
-
E.
hasTemporalClassification
chosen
Indicates a relationship where something is assigned or associated with a specific temporal category, period, or time-based classification.
- 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_69c69f327db881909a21ae3b156f8ded |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f978341081909e009c410ffc5039 |
completed | March 27, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e04c2c8190a889d928515d9b8e |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:52 p.m.