Triple
T33464861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Gargery |
E857017
|
entity |
| Predicate | teachesTradeTo |
P40765
|
FINISHED |
| Object | Pip |
—
|
NE NERFINISHED |
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: Pip | Statement: [Joe Gargery, teachesTradeTo, Pip]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachesTradeTo Context triple: [Joe Gargery, teachesTradeTo, Pip]
-
A.
providesTrainingFor
chosen
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
B.
teachableFrom
Indicates that one entity can be taught or learned from another entity, capturing a directional teachability or learnability relationship between them.
-
C.
skillTaught
Indicates that one entity teaches or imparts a particular skill to another entity.
-
D.
alsoTrains
Indicates that an entity, in addition to its primary role or activity, is involved in training another entity.
-
E.
tradesAs
Indicates that one entity conducts business or is publicly known under the trading name or brand of 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e4f996948190a20e96059d5188cc |
completed | May 3, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:37 a.m.