Triple
T1350761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Count calendar |
E28874
|
entity |
| Predicate | timeSpanCoverage |
P3058
|
FINISHED |
| Object | multi-millennial |
—
|
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: multi-millennial | Statement: [Long Count calendar, timeSpanCoverage, multi-millennial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSpanCoverage Context triple: [Long Count calendar, timeSpanCoverage, multi-millennial]
-
A.
timePeriodCoveredTo
chosen
Indicates the span or duration of time that is encompassed, addressed, or relevant to a given subject or entity.
-
B.
collectionTimespan
Indicates the time period over which a collection exists, is accumulated, or is considered valid.
-
C.
timePeriod
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
D.
coversPeriodStart
Indicates that the time span or coverage of one entity begins at, or includes, the specified starting point in time of another entity or period.
-
E.
timePeriodWithin
Indicates that one time period is entirely contained within the bounds of another time period.
- 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_69a498571d248190a0ac9eb02d97097f |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c26981d081909ca3b8d8cdf7cf2e |
completed | March 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69a4bef5857c81909ae984feb85a26ca |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.