Triple
T1306788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Autobiography |
E27896
|
entity |
| Predicate | aboutTopic |
P380
|
FINISHED |
| Object | professional football |
—
|
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: professional football | Statement: [My Autobiography, aboutTopic, professional football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aboutTopic Context triple: [My Autobiography, aboutTopic, professional football]
-
A.
featuresTopic
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
-
B.
isAbout
chosen
Indicates that one entity has as its subject, focus, or primary concern the content, topic, or theme represented by another entity.
-
C.
aboutPlace
Indicates that something (such as a statement, work, or information) concerns, describes, or is thematically related to a particular place or location.
-
D.
teachesAbout
Indicates that one entity provides instruction or information to another entity on a particular subject or topic.
-
E.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
- 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c15490a88190872c3d2698a8f9c9 |
completed | March 1, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69a4bee9e4a88190b22ab2ee831a23c9 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.