Triple
T31655536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Future Ted Mosby |
E807848
|
entity |
| Predicate | storyTopic |
P26448
|
FINISHED |
| Object | how he met their mother |
—
|
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: how he met their mother | Statement: [Future Ted Mosby, storyTopic, how he met their mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyTopic Context triple: [Future Ted Mosby, storyTopic, how he met their mother]
-
A.
topicOfDiscourse
Indicates that something serves as the subject or focus of a particular discussion, conversation, or communicative act.
-
B.
featuresTopic
chosen
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
-
C.
notableStorySubject
Indicates that the subject is a prominent or central topic, character, or element within a particular story or narrative.
-
D.
topicOfDialogue
Indicates that a particular subject or theme is the main focus of a dialogue or conversation between entities.
-
E.
storyTitle
Indicates that one entity is the title assigned to a story associated with another entity.
- 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_69f348daf95c81908b4c985b7ddcd0b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 30, 2026, 10:55 p.m.