Triple
T29827660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johnny Ingram |
E757426
|
entity |
| Predicate | hasGamblingDebt |
P170437
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Johnny Ingram, hasGamblingDebt, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGamblingDebt Context triple: [Johnny Ingram, hasGamblingDebt, true]
-
A.
hasGamblingHabitLocation
Indicates the place or setting where an entity’s gambling habit is regularly carried out or expressed.
-
B.
hasCasino
Indicates that an entity includes, contains, or is associated with a casino facility or gambling establishment.
-
C.
typeOfGambling
Indicates the specific category or form of gambling activity associated with an entity.
-
D.
gamblerInvolved
Indicates that a gambler participates in, is affected by, or is otherwise directly involved in the specified event or situation.
-
E.
hasResponsibleGamblingProgram
Indicates that an entity has implemented and maintains a program or measures aimed at promoting responsible gambling practices.
- 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_69f22457c84c8190a6d9f56bc74082a9 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f69063edbc81909e7735954aabee0b |
completed | May 3, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68f6584a88190a8c4d95c0c84bee9 |
completed | May 2, 2026, 11:57 p.m. |
Created at: April 29, 2026, 5:32 p.m.