Triple
T496797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 NWSL Championship |
E10310
|
entity |
| Predicate | homeTeamCoach |
P5835
|
FINISHED |
| Object | Mark Parsons |
E59776
|
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: Mark Parsons | Statement: [2017 NWSL Championship, homeTeamCoach, Mark Parsons]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Parsons Context triple: [2017 NWSL Championship, homeTeamCoach, Mark Parsons]
-
A.
Mark Parsons
chosen
Mark Parsons is an English football manager best known for his successful tenure leading the Portland Thorns FC in the National Women's Soccer League.
-
B.
Keith Fraase
Keith Fraase is a film editor best known for his work on the movie "Chappaquiddick."
-
C.
Ken Morris
Ken Morris is a technology entrepreneur best known as a founder of the enterprise software company PeopleSoft.
-
D.
Gary Christenson
Gary Christenson is an American local politician who serves as the mayor of Malden, Massachusetts, overseeing the city's government and community initiatives.
-
E.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f116f1b4819082f88d6c747368ae |
completed | Feb. 28, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad22fb5b30819086622f751a065b7a |
completed | March 8, 2026, 7:19 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.