Triple
T10647662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gold Medal for Humor of the American Legion |
E250877
|
entity |
| Predicate | materialOfMedal |
P95146
|
FINISHED |
| Object | gold |
—
|
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: gold | Statement: [Gold Medal for Humor of the American Legion, materialOfMedal, gold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialOfMedal Context triple: [Gold Medal for Humor of the American Legion, materialOfMedal, gold]
-
A.
materialOfTrophy
Indicates that one entity is the substance or material from which a trophy is made.
-
B.
medalType
Indicates the specific category or class of a medal associated with an award or achievement.
-
C.
medalIn
Indicates that an entity has received a medal or award in a particular event, field, or competition.
-
D.
medalSport
Indicates that a medal was awarded in a particular sport or sporting discipline.
-
E.
originalMedal
Indicates that a medal is the first or authentic instance awarded, rather than a copy, replacement, or later version.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfe29b8081908eb13637e0475ba1 |
completed | April 8, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69d6dd83b114819098e84dc658e82d7e |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df463ea8819091d6683e476b4f21 |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:05 p.m.