Triple
T12946979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darbar Sahib |
E309794
|
entity |
| Predicate | dailyVisitors |
P427
|
FINISHED |
| Object | Tens of thousands |
—
|
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: Tens of thousands | Statement: [Darbar Sahib, dailyVisitors, Tens of thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dailyVisitors Context triple: [Darbar Sahib, dailyVisitors, Tens of thousands]
-
A.
visitorCount
chosen
Indicates the number of visitors associated with a particular entity, context, or time period.
-
B.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
-
C.
hasDailyTraffic
Indicates that an entity experiences or is associated with a certain amount or pattern of traffic on a daily basis.
-
D.
countInDayApprox
Indicates an approximate number of times an event or relation occurs within a single day.
-
E.
peakDayAttendance
Indicates the number of attendees present on the single highest-attendance day within a given period or event.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:43 p.m.