Triple
T6620053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiat 131 Abarth rally car |
E149649
|
entity |
| Predicate | worldTitles |
P71562
|
FINISHED |
| Object | 1977 WRC manufacturers' championship |
—
|
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: 1977 WRC manufacturers' championship | Statement: [Fiat 131 Abarth rally car, worldTitles, 1977 WRC manufacturers' championship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldTitles Context triple: [Fiat 131 Abarth rally car, worldTitles, 1977 WRC manufacturers' championship]
-
A.
worldChampionshipTitles
Indicates the number of world championship titles an entity has won.
-
B.
mastersTitles
Indicates that one entity holds one or more master's degree titles associated with another entity (such as an institution, field, or program).
-
C.
WorldCupDisciplineTitles
Indicates the number or types of discipline-specific titles an entity has won at the World Cup.
-
D.
worldCupTitle
Indicates that an entity has won a FIFA World Cup championship title.
-
E.
worldClubChallengeTitles
Indicates the number of World Club Challenge titles an entity has won.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6bdb88cc881908f35648c15a7dc85 |
completed | March 27, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69c6ad007c1c8190af425f51011c7ad1 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6bdb76ec48190b59d576170970cc9 |
completed | March 27, 2026, 5:26 p.m. |
Created at: March 27, 2026, 1:58 p.m.