Triple
T5981195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweden women's national football team |
E133120
|
entity |
| Predicate | EuroRunnersUp |
P13987
|
FINISHED |
| Object | 1987 |
—
|
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: 1987 | Statement: [Sweden women's national football team, EuroRunnersUp, 1987]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EuroRunnersUp Context triple: [Sweden women's national football team, EuroRunnersUp, 1987]
-
A.
conferenceOfRunnerUp
Indicates the conference or league affiliation to which the runner-up entity belongs.
-
B.
regionOfRunnerUp
Indicates the geographic region associated with the runner-up in a competition or event.
-
C.
EuropeanChampionshipRunnersUp
Indicates that an entity finished in second place (as runners-up) in a European Championship competition.
-
D.
EuropeanChampionshipRunnerUpIn
chosen
Indicates that an entity finished in second place in a specified European Championship competition or edition.
-
E.
secondRoundRunnerUp
Indicates that an entity finished in third place (runner-up to the runner-up) in the second round of a competition or selection process.
- 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_69c0086f45e8819098f73dd16d45ec9d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04a67c3248190ba35a7121eb49672 |
completed | March 22, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69c049de98648190962b14fd341c93da |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:04 p.m.