Triple
T32713254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1967 NBA Finals |
E836452
|
entity |
| Predicate | venueCityGame3 |
P175499
|
FINISHED |
| Object | San Francisco |
—
|
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: San Francisco | Statement: [1967 NBA Finals, venueCityGame3, San Francisco]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: venueCityGame3 Context triple: [1967 NBA Finals, venueCityGame3, San Francisco]
-
A.
venueCityGame2
Indicates that a game (specifically the second game in a series or context) takes place in or is hosted by a particular city as its venue.
-
B.
venueCityGame1
Indicates that the venue associated with the first game is located in a particular city.
-
C.
cityOfGames
Indicates that a location is recognized as a major center or hub for games, gaming activities, or the games industry.
-
D.
game6City
Indicates that a game or sporting event took place in, or is associated with, a particular city.
-
E.
game5City
Indicates that a particular game or sporting event took place in, or is associated with, a specific city.
- 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_69f3493446148190819541f3ffe79975 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d210fc80819091ed8961aa2cddfb |
completed | May 3, 2026, 4:41 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
| PDg | Predicate description generation | batch_69f6d16b79dc8190ab0d4657f2ef9a5b |
completed | May 3, 2026, 4:39 a.m. |
Created at: May 1, 2026, 1:11 a.m.