Triple
T15693200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Admetus |
E380385
|
entity |
| Predicate | taskForMarriage |
P120312
|
FINISHED |
| Object | yoking a lion and a boar to a chariot |
—
|
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: yoking a lion and a boar to a chariot | Statement: [Admetus, taskForMarriage, yoking a lion and a boar to a chariot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: taskForMarriage Context triple: [Admetus, taskForMarriage, yoking a lion and a boar to a chariot]
-
A.
asksToMarry
Indicates that one entity proposes marriage to another, requesting that they become spouses.
-
B.
marriesFor
Indicates that one entity enters into marriage with another entity specifically for a particular reason, motive, or benefit.
-
C.
marries
Indicates that one entity enters into a legally or socially recognized marital union with another entity.
-
D.
partnerBeforeMarriage
Indicates that one entity was the romantic or life partner of another entity prior to their marriage.
-
E.
marriageContext
Indicates the situational or cultural circumstances under which a marriage occurs or exists, such as legal, social, or religious conditions surrounding the marital relationship.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0051d639481909a10614e8f83e659 |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e0b4d01c9c81909f6b611e8144c838 |
completed | April 16, 2026, 10:07 a.m. |
Created at: April 10, 2026, 4:44 a.m.