Triple
T3642925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Harbaugh |
E77231
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | John |
E55602
|
NE 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: John | Statement: [John Harbaugh, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John Harbaugh, givenName, John]
-
A.
John
chosen
John is a masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
-
B.
John
John is the nickname of John Riggins, a former American football running back best known for his Hall of Fame career with the Washington Redskins in the NFL.
-
C.
John
John is the given name of John Reith, the influential first Director-General of the BBC who shaped early public service broadcasting in the United Kingdom.
-
D.
John
John is the given name of John F. Sattler, likely referring to him in a more informal or abbreviated context.
-
E.
John
John Parke Custis was the son of Martha Washington and stepson of George Washington, known as a Virginia planter and member of the colonial gentry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc35acf2c81908f60168e93b773b1 |
completed | March 8, 2026, 6:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44f2e464881909d62dd2fad811a83 |
completed | March 13, 2026, 5:53 p.m. |
Created at: March 8, 2026, 3:24 p.m.