Triple
T24244838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adiabene |
E603334
|
entity |
| Predicate | queenHelenaContribution |
P155318
|
FINISHED |
| Object | famine relief in Jerusalem |
—
|
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: famine relief in Jerusalem | Statement: [Adiabene, queenHelenaContribution, famine relief in Jerusalem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: queenHelenaContribution Context triple: [Adiabene, queenHelenaContribution, famine relief in Jerusalem]
-
A.
relationshipToHelena
Indicates the specific type of personal, familial, or social relationship that one entity has to Helena.
-
B.
notableFemaleHero
Indicates that the subject is a female individual recognized for heroic actions or qualities that make her notably distinguished.
-
C.
mythologicalQueen
Indicates that one entity is a queen who exists within mythology, legend, or folklore rather than historical reality.
-
D.
roleInHecuba
Indicates that an entity has a specific role or character assignment in the play *Hecuba*.
-
E.
relationshipToHecuba
Indicates a familial or social connection that an entity has with Hecuba.
- 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_69e2953f631c819097cbb421046bd417 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28b84707881908b358aa38fafb61a |
completed | April 29, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 18, 2026, 12:04 a.m.