Triple
T32989603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syracuse Orange men’s cross country |
E844046
|
entity |
| Predicate | conferenceTeamChampionshipsACC |
P59751
|
FINISHED |
| Object | 2013 |
—
|
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: 2013 | Statement: [Syracuse Orange men’s cross country, conferenceTeamChampionshipsACC, 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conferenceTeamChampionshipsACC Context triple: [Syracuse Orange men’s cross country, conferenceTeamChampionshipsACC, 2013]
-
A.
collegeTeamChampionships
chosen
Indicates the championships or titles that a college sports team has won.
-
B.
collegeChampionshipTeam
Indicates that a team is the winner of a specified college-level championship competition.
-
C.
nationalChampionshipParticipation
Indicates that an entity has taken part in a national-level championship competition.
-
D.
FAcupTitles
Indicates that an entity has won a specified number of FA Cup titles.
-
E.
conferenceChampionshipsInCollege
Indicates the number of conference championships an entity won during its college career.
- 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_69f3494d99988190b502c68926af2c4d |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 1, 2026, 1:22 a.m.