Triple
T17308990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eduardo Hurtado |
E420240
|
entity |
| Predicate | leagueGoalsScoredForTeam |
P9098
|
FINISHED |
| Object | LA Galaxy in Major League Soccer |
—
|
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: LA Galaxy in Major League Soccer | Statement: [Eduardo Hurtado, leagueGoalsScoredForTeam, LA Galaxy in Major League Soccer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leagueGoalsScoredForTeam Context triple: [Eduardo Hurtado, leagueGoalsScoredForTeam, LA Galaxy in Major League Soccer]
-
A.
goalScorerTeam
Indicates that a team is the one for which a particular goal scorer scored a goal.
-
B.
championsGoalsFor
Indicates that an entity actively supports, advocates for, or works to advance the goals of another entity.
-
C.
topGoalScorerGoals
Indicates the number of goals scored by the top goal scorer in a given context or competition.
-
D.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
E.
leagueGoalsForArsenal
Indicates the number of league goals scored by Arsenal.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43900eca88190930af0e4ec4fc0f9 |
completed | April 19, 2026, 2:08 a.m. |
| PD | Predicate disambiguation | batch_69e3b01b9d1c8190a406dd941c9b11a1 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:43 a.m.