Triple
T10627551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Children of Hermes |
E250360
|
entity |
| Predicate | hasNotableMember |
P304
|
FINISHED |
| Object | Daphnis (in some traditions) |
E520746
|
NE 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: Daphnis (in some traditions) | Statement: [Children of Hermes, hasNotableMember, Daphnis (in some traditions)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daphnis (in some traditions) Context triple: [Children of Hermes, hasNotableMember, Daphnis (in some traditions)]
-
A.
Daphnis
chosen
Daphnis is a young shepherd and one of the two pastoral lovers at the center of the ancient Greek romance "Daphnis and Chloe."
-
B.
Daphnis
Daphnis is a small moon of Saturn that orbits within the planet’s rings and gravitationally sculpts the edges of the Keeler Gap.
-
C.
Daphne
Daphne is a coastal city in Baldwin County, Alabama, situated along the eastern shore of Mobile Bay.
-
D.
Daphne
Daphne is a nymph from Greek mythology best known for being pursued by Apollo and transformed into a laurel tree to escape him.
-
E.
Daphne
Daphne is an HTTP, HTTP/2, and WebSocket server for ASGI applications, commonly used to serve Django and other Python async web frameworks.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df9228088190bdd57a95d8671618 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96ba260b48190a5bde201ee3df69a |
completed | April 10, 2026, 9:29 p.m. |
Created at: April 8, 2026, 8:55 p.m.