Triple
T3947946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Half Marathon |
E84791
|
entity |
| Predicate | typicalParticipantsNumber |
P1131
|
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: [Paris Half Marathon, typicalParticipantsNumber, tens of thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalParticipantsNumber Context triple: [Paris Half Marathon, typicalParticipantsNumber, tens of thousands]
-
A.
typicalGroupSizeRange
Indicates the usual minimum and maximum number of individuals that typically occur together in a group for the given entity.
-
B.
numberOfPersons
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
-
C.
numberOfParticipants
chosen
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
D.
guestCountApproximate
Indicates that the number of guests involved is represented as an estimated or approximate count rather than an exact figure.
-
E.
typicalMembers
Indicates that the related entities are representative or characteristic members of a larger group, category, or class.
- 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaa5afdc8190b709af2473d75d02 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8ed04e4819096bced8971cd888d |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:30 p.m.