Triple
T34937534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teddy McArdle |
E1007617
|
entity |
| Predicate | settingOfMajorScenes |
P107448
|
FINISHED |
| Object | ocean liner |
—
|
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: ocean liner | Statement: [Teddy McArdle, settingOfMajorScenes, ocean liner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfMajorScenes Context triple: [Teddy McArdle, settingOfMajorScenes, ocean liner]
-
A.
scenes
chosen
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
-
B.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
C.
numberOfScenes
Indicates the total count of distinct scenes associated with or contained within an entity.
-
D.
mainSettingOfStory
Indicates that a location or environment serves as the primary setting in which the events of a story take place.
-
E.
isSettingOfScene
Indicates that a particular location, time, or environment serves as the backdrop or context in which a scene takes place.
- 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_69f76dc513fc819084a1ff52abbfa5bc |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: May 3, 2026, 4 p.m.