Triple
T6488435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acrisius |
E146572
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Proetus |
E588847
|
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: Proetus | Statement: [Acrisius, sibling, Proetus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Proetus Context triple: [Acrisius, sibling, Proetus]
-
A.
Proetus
chosen
Proetus is a king in Greek mythology, often associated with the city of Tiryns and known for his conflicts with his twin brother Acrisius and his role in the story of Bellerophon.
-
B.
Lynceus
Lynceus is a figure in Greek mythology renowned as one of the Argonauts, famed for his exceptionally keen eyesight.
-
C.
Phorcydes
Phorcydes is a primordial sea-deity figure from Greek mythology, often associated with ancient oceanic powers and monstrous offspring.
-
D.
Mardontes
Mardontes was a Persian military commander who led Achaemenid forces against the Greeks during the Greco-Persian Wars, notably at the Battle of Mycale.
-
E.
Iberus
Iberus is the ancient Latin name for the Ebro River, one of the major rivers of the Iberian Peninsula in present-day Spain.
- 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_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a97fff88190b6f993c14df62649 |
completed | March 22, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c653b792f48190b301cdc643db8ddf |
completed | March 27, 2026, 9:53 a.m. |
Created at: March 22, 2026, 4:52 p.m.