Triple
T16138488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ludo Bagman |
E391590
|
entity |
| Predicate | gamblingHabit |
P16449
|
FINISHED |
| Object | Owes gold to goblins |
—
|
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: Owes gold to goblins | Statement: [Ludo Bagman, gamblingHabit, Owes gold to goblins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gamblingHabit Context triple: [Ludo Bagman, gamblingHabit, Owes gold to goblins]
-
A.
hasGamblingHabitLocation
Indicates the place or setting where an entity’s gambling habit is regularly carried out or expressed.
-
B.
typeOfGambling
Indicates the specific category or form of gambling activity associated with an entity.
-
C.
drinkingHabit
Indicates an entity’s typical pattern or frequency of consuming alcoholic or other beverages.
-
D.
addiction
chosen
Indicates a compulsive dependence of one entity on a substance, activity, or behavior, typically despite negative consequences and difficulty stopping.
-
E.
gamblerInvolved
Indicates that a gambler participates in, is affected by, or is otherwise directly involved in the specified event or situation.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a06e0988190b5cd62d422d058a2 |
completed | April 17, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69e182885bc08190822ae7e8a4b8ac1f |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.