Triple
T11445926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gemma McCaw |
E271262
|
entity |
| Predicate | hasGivenPublicTalksOn |
P10206
|
FINISHED |
| Object | health and wellness |
—
|
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: health and wellness | Statement: [Gemma McCaw, hasGivenPublicTalksOn, health and wellness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGivenPublicTalksOn Context triple: [Gemma McCaw, hasGivenPublicTalksOn, health and wellness]
-
A.
spokeAt
chosen
Indicates that a person delivered a talk, speech, or presentation at a particular event or location.
-
B.
gaveLecturesAt
Indicates that a person delivered lectures or taught courses at a particular institution or location.
-
C.
lecturesHeldIn
Indicates that a lecture event takes place or is conducted within a specific location or venue.
-
D.
hasNotablePublicationType
Indicates that an entity is associated with a publication of a specific notable type or category.
-
E.
succeededAsSpeakerBy
Indicates that one entity took over the role or position of speaker from another entity as their successor.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8088a66f48190b2b4a56cd62097cf |
completed | April 9, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69d7e7162b288190a0bfb89f7eb747c7 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:35 p.m.