Triple
T7324579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aegeus |
E168836
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Lycus |
E71302
|
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: Lycus | Statement: [Aegeus, sibling, Lycus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lycus Context triple: [Aegeus, sibling, Lycus]
-
A.
Lycus
chosen
Lycus is a figure in Greek mythology, traditionally known as a son of the Pleiad Celaeno and the god Poseidon.
-
B.
Lynceus
Lynceus is a figure in Greek mythology renowned as one of the Argonauts, famed for his exceptionally keen eyesight.
-
C.
Lykosoura
Lykosoura was an ancient Arcadian city in the Peloponnese, renowned as a major sanctuary site dedicated to the goddess Despoina in Greek religion.
-
D.
Melesias
Melesias is a character in Plato’s dialogue "Laches," portrayed as a concerned Athenian father seeking guidance on the proper education of his son.
-
E.
Aegialos
Aegialos was the ancient name of the Greek city-state later known as Sicyon, located in the northern Peloponnese.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f04993408190b73fb46d83a632d5 |
completed | March 27, 2026, 9:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ef0a1200819089fe3e18493d8bee |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 3:03 p.m.