Triple
T8449041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lance Fortnow |
E199753
|
entity |
| Predicate | blogTopic |
P12980
|
FINISHED |
| Object | computational complexity theory |
—
|
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: computational complexity theory | Statement: [Lance Fortnow, blogTopic, computational complexity theory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: blogTopic Context triple: [Lance Fortnow, blogTopic, computational complexity theory]
-
A.
featuresTopic
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
-
B.
primaryTopicOf
chosen
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
C.
frequentlyDiscussedIn
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
-
D.
exampleTopic
Indicates that something serves as an illustrative or representative instance of a broader topic or concept.
-
E.
categoryFocus
Indicates that one entity is the primary subject, theme, or focal point within the broader category defined by the other 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe445b7988190b53ae45070c70d1d |
completed | March 31, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:09 p.m.