Triple
T923290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fortune Global 500 |
E19928
|
entity |
| Predicate | timeReference |
P1936
|
FINISHED |
| Object | preceding fiscal year |
—
|
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: preceding fiscal year | Statement: [Fortune Global 500, timeReference, preceding fiscal year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeReference Context triple: [Fortune Global 500, timeReference, preceding fiscal year]
-
A.
timeOffsetReference
Indicates that a temporal value is specified relative to a particular reference time or event, defining the offset between them.
-
B.
timeSystem
Indicates a relationship where an entity uses, follows, or is defined within a particular system for measuring or organizing time.
-
C.
time
chosen
Indicates a temporal relationship specifying when an event occurs or how entities are ordered or related in time.
-
D.
timeCoordinateType
Indicates the specific temporal reference system or framework used to define and interpret time coordinates for an event or entity.
-
E.
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).
- 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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b314f6fc81908a3ccc2e741e3c2b |
completed | March 1, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69a4b295b02481908e5f53bfcb83cc94 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.