Triple
T423530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MLS Cup 2014 |
E8155
|
entity |
| Predicate | homeTeamPreviousTitles |
P13594
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [MLS Cup 2014, homeTeamPreviousTitles, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeTeamPreviousTitles Context triple: [MLS Cup 2014, homeTeamPreviousTitles, 4]
-
A.
team1ConferenceTitles
Indicates the number of conference championship titles won by the first team in a given context or comparison.
-
B.
previousTeamNamesAlsoAssociatedWithFranchise
Indicates that the earlier team names are also historically or officially linked to the same franchise.
-
C.
team1LaterKnownAs
Indicates that the first team was later renamed to or became known by the identity of the second team.
-
D.
formerSportsTeam
Indicates that an entity was once a member of or played for a particular sports team in the past but no longer does so.
-
E.
team2ConferenceTitles
Indicates the number of conference championship titles that the second team has won.
- F. None of above. chosen
Provenance (4 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eec200648190bcb9f1b98c8e9cdf |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd5439c8190aea661b8b4aa51e9 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2ee8b56d08190bd625626353d01b4 |
completed | Feb. 28, 2026, 1:32 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.