Triple
T14216137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eurypylus |
E352355
|
entity |
| Predicate | deathContextInOtherTraditions |
P90208
|
FINISHED |
| Object | slain in battle at Troy |
—
|
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: slain in battle at Troy | Statement: [Eurypylus, deathContextInOtherTraditions, slain in battle at Troy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathContextInOtherTraditions Context triple: [Eurypylus, deathContextInOtherTraditions, slain in battle at Troy]
-
A.
traditionalMannerOfDeath
Indicates that an entity died in a way that follows or reflects a culturally recognized or customary method of death.
-
B.
deathTypeInFiction
chosen
Indicates the manner or category of how a character dies within a fictional narrative.
-
C.
deathInterpretedAs
Indicates that one entity’s death is understood, framed, or interpreted in a particular way by another entity or within a given context.
-
D.
traditionalPlaceOfDeath
Indicates the location where a person is customarily or culturally considered to have died, according to traditional or historical accounts.
-
E.
deathInFiction
Indicates that an entity’s death occurs within a fictional work or narrative rather than in real life.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6210213481908fac6893e8a9f143 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:06 a.m.