Triple
T19330236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BoardWalk view |
E483467
|
entity |
| Predicate | typicalGuest |
P44542
|
FINISHED |
| Object | guests wanting views of the boardwalk activity |
—
|
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: guests wanting views of the boardwalk activity | Statement: [BoardWalk view, typicalGuest, guests wanting views of the boardwalk activity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalGuest Context triple: [BoardWalk view, typicalGuest, guests wanting views of the boardwalk activity]
-
A.
typicalGuests
chosen
Indicates the usual or most common guests associated with a particular host, place, or event.
-
B.
typicalGuestConfederation
Indicates that one entity is typically a guest or participant within the confederation represented by the other entity.
-
C.
guestStar
Indicates that one entity appears in a limited, special, or featured role within another entity’s production, event, or context, without being a regular or primary participant.
-
D.
typicalSpeaker
Indicates that the subject is a prototypical or characteristic speaker or source of utterances in the context of the object.
-
E.
recurringGuestIn
Indicates that an entity appears repeatedly as a guest in a particular context, such as a show, event, or series.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e616412bcc81909bb34d3cf5363129 |
completed | April 20, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
Created at: April 10, 2026, 1:33 p.m.