Triple
T36968383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doug Stanhope |
E914489
|
entity |
| Predicate | oftenTopics |
P5303
|
FINISHED |
| Object | drugs |
—
|
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: drugs | Statement: [Doug Stanhope, oftenTopics, drugs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenTopics Context triple: [Doug Stanhope, oftenTopics, drugs]
-
A.
coveredTopics
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
-
B.
frequentlyDiscussedIn
chosen
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
-
C.
topicOfDiscourse
Indicates that something serves as the subject or focus of a particular discussion, conversation, or communicative act.
-
D.
topicOfDialogue
Indicates that a particular subject or theme is the main focus of a dialogue or conversation between entities.
-
E.
oftenSoughtOn
Indicates that one entity is frequently searched for, requested, or pursued in relation to 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_69f76e8c498c8190b2842db80aea8b3b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe12a899d4819080d48423f32eace9 |
completed | May 8, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69fe0d7f6aa08190a1d2dfc025d4e0dc |
completed | May 8, 2026, 4:21 p.m. |
Created at: May 3, 2026, 4:14 p.m.