Triple
T13707994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harrah's Philadelphia Casino & Racetrack |
E328693
|
entity |
| Predicate | hasGamingType |
P10208
|
FINISHED |
| Object | slot machines |
—
|
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: slot machines | Statement: [Harrah's Philadelphia Casino & Racetrack, hasGamingType, slot machines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGamingType Context triple: [Harrah's Philadelphia Casino & Racetrack, hasGamingType, slot machines]
-
A.
hasGameType
Indicates that an entity (such as a game or match) is associated with a specific category or type of game.
-
B.
includesGameType
chosen
Indicates that one entity contains or supports a particular type or category of game.
-
C.
hasGamesAt
Indicates that a particular location, venue, or platform hosts or offers one or more games.
-
D.
supportsGames
Indicates that an entity is capable of running, handling, or being compatible with one or more games.
-
E.
hasPlayType
Indicates the type or category of play associated with an event, action, or performance.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dcad18d48c8190a26be865c31975d6 |
completed | April 13, 2026, 8:45 a.m. |
| PD | Predicate disambiguation | batch_69dbbe92d77c81908e0244cffb7f78c5 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:54 p.m.