Triple
T2379328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonah Lomu |
E46273
|
entity |
| Predicate | nationalTeamTries |
P38359
|
FINISHED |
| Object | 37 |
—
|
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: 37 | Statement: [Jonah Lomu, nationalTeamTries, 37]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalTeamTries Context triple: [Jonah Lomu, nationalTeamTries, 37]
-
A.
nationalTeamAppearances
Indicates the number of official matches in which an entity has represented its national team.
-
B.
nationalFootballTeam
Indicates that one entity is the official football (soccer) team representing the other entity at the national level.
-
C.
previousNationalTeamEntity
Indicates that an entity previously represented a particular national team before its current or later affiliation.
-
D.
nationalTeamSystem
Indicates a relationship where an entity is part of, governed by, or operates within a specific national team structure or organizational system.
-
E.
nationalTeamYears
Indicates the span of years during which an entity was active as a member of a national team.
- F. None of above. chosen
Provenance (4 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7b60c8c819080e4f682e4362a93 |
completed | March 7, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69abc59f73f08190924a36d7d475d8f4 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6f4245881909282b3184a288e2a |
completed | March 7, 2026, 6:34 a.m. |
Created at: March 4, 2026, 7:57 p.m.