Triple
T32250186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Randall |
E823858
|
entity |
| Predicate | hasEntertainmentHistory |
P190366
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [North Randall, hasEntertainmentHistory, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEntertainmentHistory Context triple: [North Randall, hasEntertainmentHistory, yes]
-
A.
hasHistoryChannel
Indicates that an entity possesses or provides access to a television or media channel dedicated to historical content.
-
B.
hasHistoricalSee
Indicates that one entity historically served as the episcopal see or central seat of authority for another entity, typically a diocese or bishopric.
-
C.
hasRecordingHistory
Indicates that an entity has an associated record of past recordings or recorded events.
-
D.
hasHistoricity
Indicates that something possesses historical existence, significance, or authenticity, rather than being purely fictional, mythical, or timeless.
-
E.
hasPartInFilmHistory
Indicates that an entity has played a role or contributed in some way to the history or development of film.
- 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_69f3490cdda88190a9d61e11252a771f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc4b5f22c8190b8b256adbdc2570c |
completed | May 7, 2026, 4:58 p.m. |
Created at: May 1, 2026, 12:40 a.m.