Triple
T5547040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gambler |
E145433
|
entity |
| Predicate | featuresGame |
P65304
|
FINISHED |
| Object | roulette |
—
|
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: roulette | Statement: [The Gambler, featuresGame, roulette]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresGame Context triple: [The Gambler, featuresGame, roulette]
-
A.
videoGame
Indicates that one entity is a video game associated with, created by, or otherwise related to another entity.
-
B.
relatedGame
Indicates that one game has a notable connection or association with another game, such as shared content, themes, or series.
-
C.
featuresFictionalSport
Indicates that a work includes or showcases a fictional sport as part of its content or setting.
-
D.
featuresBattle
Indicates that one entity includes, presents, or involves a battle as a significant element or event.
-
E.
games
Indicates that one entity participates in, is associated with, or is characterized by playing or engaging in games with another entity.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fdec3588190b0af7d2ca8e8ee9b |
completed | March 22, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69c01b0e72f08190bf705d8fe1639401 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f051e508190b3886d87b4afdd0b |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:35 p.m.