Triple
T5894041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GDAXI |
E131059
|
entity |
| Predicate | timeSeriesType |
P14858
|
FINISHED |
| Object | price index |
—
|
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: price index | Statement: [GDAXI, timeSeriesType, price index]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSeriesType Context triple: [GDAXI, timeSeriesType, price index]
-
A.
timeType
Indicates the specific temporal category or classification associated with a time-related entity or value (e.g., duration, point in time, interval, or recurrence type).
-
B.
seriesType
chosen
Indicates the classification or category of a series that an entity belongs to or is associated with.
-
C.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
-
D.
timescale
Indicates the temporal scale or duration over which a process, relationship, or effect occurs or is evaluated.
-
E.
timeContinuousOrDiscrete
Indicates whether the time dimension in a given context is modeled as a continuous flow or as discrete, separate time points.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0334dc8248190b7394dcece362d52 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:58 p.m.