Triple
T19971471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luxembourg at the Olympic Games |
E480084
|
entity |
| Predicate | hasAthletesIn |
P17934
|
FINISHED |
| Object | track and field |
—
|
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: track and field | Statement: [Luxembourg at the Olympic Games, hasAthletesIn, track and field]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAthletesIn Context triple: [Luxembourg at the Olympic Games, hasAthletesIn, track and field]
-
A.
hasAthlete
chosen
Indicates a relationship where an entity (such as a team, organization, or event) includes or is associated with one or more athletes.
-
B.
athletesFrom
Indicates that one or more athletes originate from, represent, or are associated with a particular place or organization.
-
C.
hasOlympians
Indicates that an entity includes, is associated with, or contains one or more Olympian participants or members.
-
D.
hasAthletics
Indicates that an entity participates in, is associated with, or offers athletics-related activities or programs.
-
E.
hasPartnerInSport
Indicates that one entity has another entity as a partner with whom they jointly participate in a sport or sporting activity.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc9694881909a31841702ab9e5f |
completed | April 20, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.