Triple
T27203670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watkins Family Hour |
E683803
|
entity |
| Predicate | cityOfRegularVenue |
P15624
|
FINISHED |
| Object | Los Angeles |
—
|
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: Los Angeles | Statement: [Watkins Family Hour, cityOfRegularVenue, Los Angeles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityOfRegularVenue Context triple: [Watkins Family Hour, cityOfRegularVenue, Los Angeles]
-
A.
cityOfVenue
Indicates the city in which a given venue is located.
-
B.
typicalVenueCity
chosen
Indicates that a particular city is the usual or standard location where an event, activity, or organization is typically held or based.
-
C.
isRegularVenueFor
Indicates that a location is commonly or routinely used as the venue for a particular event, activity, or entity’s gatherings.
-
D.
typicalVenueMetroArea
Indicates the metropolitan area where an entity is most commonly or characteristically located or hosted.
-
E.
usualVenueSince
Indicates that a particular venue has been the regular or customary location for something (e.g., an event or activity) starting from a specified point in time.
- 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_69eefad1fd5c8190a4a46ea6afe58bfa |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 9:37 a.m.