Triple
T37322328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pueblito |
E926514
|
entity |
| Predicate | estimatedPeakOccupation |
P178418
|
FINISHED |
| Object | around 13th to 16th centuries |
—
|
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: around 13th to 16th centuries | Statement: [Pueblito, estimatedPeakOccupation, around 13th to 16th centuries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedPeakOccupation Context triple: [Pueblito, estimatedPeakOccupation, around 13th to 16th centuries]
-
A.
peakOccupation
chosen
Indicates the time or context in which an entity reaches its highest level of activity, usage, or occupancy.
-
B.
hasNumberOfSeatsAtPeak
Indicates the maximum number of seats available or occupied at the peak usage or capacity of something.
-
C.
numberOfSeatsPeakApprox
Indicates an approximate count of seats available or occupied during peak usage or demand periods.
-
D.
deploymentPeakNumber
Indicates the maximum number of deployments (or deployment instances) reached during a specified period or under given conditions.
-
E.
numberOfEmployeesAtPeak
Indicates the highest recorded count of employees that an entity had at any point in time.
- 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_69f76eb28af88190b093b32e3fd614ab |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:16 p.m.