Triple
T16646164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Judd |
E404475
|
entity |
| Predicate | guernseyNumberAtWestCoast |
P2651
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Chris Judd, guernseyNumberAtWestCoast, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: guernseyNumberAtWestCoast Context triple: [Chris Judd, guernseyNumberAtWestCoast, 3]
-
A.
guernseyNumberAtPortAdelaide
Indicates the guernsey (jersey) number that a player wears when playing for the Port Adelaide football club.
-
B.
countryCoast
Indicates that a country has a coastline along a sea or ocean.
-
C.
connectsToCoastAt
Indicates that one entity has a direct physical or geographical connection or access to a coastline at the location of another entity.
-
D.
countryCoastDesigned
Indicates that a country’s coastline was intentionally planned, shaped, or engineered according to a particular design or layout.
-
E.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad59540819093765b7a67320f72 |
completed | April 18, 2026, 12:36 p.m. |
| PD | Predicate disambiguation | batch_69e296af2f88819092c9ffee4a65d7dd |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:18 a.m.