Triple
T31937151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Creon of Corinth |
E815421
|
entity |
| Predicate | deathCauseInMedea |
P144
|
FINISHED |
| Object | contact with poisoned garments |
—
|
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: contact with poisoned garments | Statement: [Creon of Corinth, deathCauseInMedea, contact with poisoned garments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathCauseInMedea Context triple: [Creon of Corinth, deathCauseInMedea, contact with poisoned garments]
-
A.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
-
B.
causeOfDeath
chosen
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
C.
motherDeath
Indicates that the mother of the referenced individual has died.
-
D.
causeOfMothersDeath
Indicates that the subject is the specific cause responsible for the mother’s death.
-
E.
deifiedPersonDeathCause
Indicates the cause or manner of death of the person who is venerated or treated as a deity.
- 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_69f348f3035c81908558e2339955abb3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 12:05 a.m.