Triple
T2779429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Analytical Writing |
E61655
|
entity |
| Predicate | scoredBy |
P43135
|
FINISHED |
| Object | human raters |
—
|
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: human raters | Statement: [Analytical Writing, scoredBy, human raters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoredBy Context triple: [Analytical Writing, scoredBy, human raters]
-
A.
scoredFor
Indicates that one entity achieved points or a score on behalf of another entity, such as a player scoring for a team.
-
B.
hasScoredFor
Indicates that one entity has scored points, goals, or similar achievements on behalf of another entity, such as a team, organization, or side.
-
C.
goalScorer
Indicates that the subject is the player who scored a particular goal in a game or match.
-
D.
scoredInMatch
Indicates that an entity (typically a player or team) scored during a particular match.
-
E.
decisiveTouchdownScorer
Indicates the player who scored the touchdown that ultimately determined the outcome of the game.
- 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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdd00b65c8190a8ea444308c4fa2b |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abddcc348081908b5f760899389d4f |
completed | March 7, 2026, 8:11 a.m. |
Created at: March 6, 2026, 9:57 p.m.