Triple
T6287701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argonautic expedition |
E140940
|
entity |
| Predicate | hasKeyFigure |
P810
|
FINISHED |
| Object | Argus |
E281791
|
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: Argus | Statement: [Argonautic expedition, hasKeyFigure, Argus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Argus Context triple: [Argonautic expedition, hasKeyFigure, Argus]
-
A.
Argus
Argus is an early distributed programming language known for pioneering concepts in fault-tolerant, distributed systems and influencing modern object-oriented and concurrent programming.
-
B.
Argus
chosen
Argus is a many-eyed giant from Greek mythology best known for his role as a vigilant guardian.
-
C.
Aidoneus
Aidoneus is an alternate name and epithet for Hades, the Greek god who rules the underworld and the dead.
-
D.
Phineus
Phineus is a figure in Greek mythology known primarily as a blind seer and king tormented by the Harpies until aided by the Argonauts.
-
E.
Orthrus
Orthrus is a two-headed dog from Greek mythology, often associated with the giant Geryon and slain by the hero Heracles.
- 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_69c008cd17c8819082b82d3fbeb68047 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063ff9f74819088dc603f56fc930c |
completed | March 22, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c51973a364819099dc5a99858e9a7a |
completed | March 26, 2026, 11:33 a.m. |
Created at: March 22, 2026, 4:26 p.m.