Triple
T14456563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Garden Birdwatch |
E358473
|
entity |
| Predicate | typicalParticipantsPerYear |
P1131
|
FINISHED |
| Object | hundreds of thousands of people |
—
|
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: hundreds of thousands of people | Statement: [Big Garden Birdwatch, typicalParticipantsPerYear, hundreds of thousands of people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalParticipantsPerYear Context triple: [Big Garden Birdwatch, typicalParticipantsPerYear, hundreds of thousands of people]
-
A.
typicalNumberOfRecipientsPerYear
Indicates the usual or average count of recipients involved in or affected by something within a one-year period.
-
B.
typicalVisitorsPerSeason
Indicates the usual number of visitors associated with each season for a given entity or location.
-
C.
numberOfParticipants
chosen
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
D.
typicalNumberOfMeetingsPerSeason
Indicates the usual or average count of meetings that occur within a single season.
-
E.
typicalParty
Indicates that an entity is a usual, standard, or characteristic participant in a given type of event, situation, or relationship.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91a9c0d48190ae015e5e0db806ca |
completed | April 14, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69de5c42bd3c81909a62acf30cc24d1e |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:19 a.m.