Triple
T32224256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robbie Deans |
E823151
|
entity |
| Predicate | teamTitlesWonWith |
P173854
|
FINISHED |
| Object | Crusaders |
—
|
NE NERFINISHED |
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: Crusaders | Statement: [Robbie Deans, teamTitlesWonWith, Crusaders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamTitlesWonWith Context triple: [Robbie Deans, teamTitlesWonWith, Crusaders]
-
A.
teamWithTitles
Indicates a relationship where a team is associated with one or more titles it has earned or holds.
-
B.
teamWithMultipleTitles
Indicates that a team has won more than one title or championship within the relevant competition or context.
-
C.
team2LeagueTitles
Indicates that a given team has won a specified number of league titles.
-
D.
mostTitlesTeamTitles
Indicates that the referenced team holds the highest number of titles compared to all other teams in the specified context.
-
E.
team2LeagueTitlesContext
Indicates that the second team has won league titles within a specified contextual scope (such as a particular time period, competition, or condition).
- 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_69f3490b4f948190b99e4f999f5be25f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bbc8c6c881908ce99e774c010ff5 |
completed | May 3, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b960ca4081909a77690c2b122f5e |
completed | May 3, 2026, 2:56 a.m. |
Created at: May 1, 2026, 12:38 a.m.