Triple
T13869214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France national rugby sevens team |
E333405
|
entity |
| Predicate | numberOfPlayersOnField |
P39852
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [France national rugby sevens team, numberOfPlayersOnField, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPlayersOnField Context triple: [France national rugby sevens team, numberOfPlayersOnField, 7]
-
A.
playersPerSideOnField
chosen
Indicates the number of players from each team that are simultaneously present on the field during play.
-
B.
usesNumberOfPlayersOnFieldPerTeam
Indicates that the relationship specifies or depends on how many players each team has on the field at a given time.
-
C.
playerNumber
Indicates the specific jersey or identification number assigned to a player within a team or game context.
-
D.
minimumFemalePlayersOnField
Indicates the rule that specifies the least number of female players that must be present on the field at any given time.
-
E.
numberOfPlayersPerTeam
Indicates the quantity of players that are assigned to or allowed on each team in a given context.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a101488190bd790b28033d38b9 |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69de05972f3881909977b4c843984f88 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:14 p.m.