Triple
T33887907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Becán |
E868678
|
entity |
| Predicate | approximateOccupationPeak |
P195414
|
FINISHED |
| Object | Late Classic period |
—
|
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: Late Classic period | Statement: [Becán, approximateOccupationPeak, Late Classic period]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateOccupationPeak Context triple: [Becán, approximateOccupationPeak, Late Classic period]
-
A.
approximateOccupation
Indicates that one entity is inferred or estimated to be the occupation or job role of another entity, rather than being known with certainty.
-
B.
peakOccupation
Indicates the time or context in which an entity reaches its highest level of activity, usage, or occupancy.
-
C.
hasPeakOccupation
chosen
Indicates that an entity reached its highest level of activity, prominence, or engagement during a specified time period or context.
-
D.
approximateUserPeak
Indicates that one value or event is an estimated or inferred maximum point associated with a particular user.
-
E.
numberOfSeatsPeakApprox
Indicates an approximate count of seats available or occupied during peak usage or demand periods.
- 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_69f34996761c8190864e42f7c9cf215b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fefa064ab48190925759950d0d94d9 |
completed | May 9, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69fef96ae5d08190b027435753c44821 |
completed | May 9, 2026, 9:07 a.m. |
Created at: May 1, 2026, 1:48 a.m.